Detect to Track and Track to Detect

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 73,472

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812

You Only Look Once: Unified, Real-Time Object Detection

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803

Going deeper with convolutions

Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460

ImageNet Large Scale Visual Recognition Challenge

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380

Fully convolutional networks for semantic segmentation

Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834

Spatial-Temporal Memory Networks for Video Object Detection

Xiao, F., & Lee, Y. J. (2017) · Cited by 5

Multi-Object Tracking with Tracked Object Bounding Box Association

Yang, N., Wang, Y., & Chau, L. (2021) · IEEE International Conference on Multimedia & Expo Workshops (ICMEW) · doi:10.1109/icmew53276.2021.9455993 · Cited by 5

Temporal feature enhancement network with external memory for live-stream video object detection

Fujitake, M., & Sugimoto, A. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108847 · Cited by 5

Tracking Different Ant Species: An Unsupervised Domain Adaptation Framework and a Dataset for Multi-object Tracking

Abeysinghe, C., Reid, C. R., Rezatofighi, H., & Meyer, B. (2023) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/61 · Cited by 5

Pedestrian detection with motion features via two-stream ConvNets

Yoshihashi, R., Trinh, T. T., Kawakami, R., You, S., Iida, M., & Naemura, T. (2018) · IPSJ Transactions on Computer Vision and Applications · doi:10.1186/s41074-018-0048-5 · Cited by 5

Convolutional Neural Network-based Simple Online Multiple Object Tracking

Wang, J., Zeng, X., & An, W. (2018) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/compcomm.2018.8780631 · Cited by 5

Traffic Sign Recognition on Video Sequence using Deep Neural Networks and Matching Algorithm

Belkin, I., Tkachenko, S. N., & Yudin, D. A. (2019) · International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI) · doi:10.1109/ic-aiai48757.2019.00013 · Cited by 5

Spatial-Temporal Feature Aggregation Network For Video Object Detection

Zhu, C. G., Li, W., Fei, C., Liu, B., & Yu, N. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054080 · Cited by 5

Imitation-Based Active Camera Control with Deep Convolutional Neural Network

Kyrkou, C. (2020) · IEEE International Conference on Image Processing, Applications and Systems (IPAS) · doi:10.1109/ipas50080.2020.9334958 · Cited by 5

DA-SACOT: Domain adaptive-segmentation guided attention for correlation based object tracking

Raju, P. M., Mishra, D., & Mukherjee, P. (2021) · Image and Vision Computing · doi:10.1016/j.imavis.2021.104215 · Cited by 5

Detector–tracker integration framework and attention mechanism for multi–object tracking

Li, C., Chen, G., Gou, R., & Tang, Z. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.08.107 · Cited by 5

Survey of video object detection algorithms based on deep learning

Lu, Z., Zhou, T., Jiang, R., & Peng, Y. (2021) · International Conference on Algorithms, Computing and Artificial Intelligence (ACAI) · doi:10.1145/3508546.3508622 · Cited by 5

CyLKs: Unsupervised Cycle Lucas-Kanade Network for Landmark TrackingPreprint

Weng, X., & Han, W. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.11325 · Cited by 5

An Improved Multi-Object Tracking Algorithm Designed for Complex Environments

Liu, W., Yao, J., Jiang, F., & Wang, M. (2025) · Sensors · doi:10.3390/s25175325 · Cited by 4

METFormer: A Motion Enhanced Transformer for Multiple Object Tracking

Gao, J., Yap, K., Wang, Y., Garg, K., & Han, B. S. (2023) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas46773.2023.10182032 · Cited by 4

Video object detection via space–time feature aggregation and result reuse

Duan, L., Yang, R. L. T. X. W., Yue, K., Sun, Z., & Yuan, G. (2024) · IET Image Processing · doi:10.1049/ipr2.13179 · Cited by 4

Multi-object tracking with robust object regression and association

Li, Y., Ji, H., Chen, X., Lai, Y., & Yang, Y. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103586 · Cited by 4

Enhancing Thermal MOT: A Novel Box Association Method Leveraging Thermal Identity and Motion Similarity

Ahmar, W. E., Kolhatkar, D., Nowruzi, F. E., & Laganière, R. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-91575-8_7 · Cited by 4

Multi-Object Tracking With Memory Fusion in UAV Videos

Cui, Y., Li, S., Yang, X., & Wang, G. (2025) · IEEE Access · doi:10.1109/access.2025.3596684 · Cited by 4

TSSD: Temporal Single-Shot Object Detection Based on Attention-Aware LSTM.

Chen, X., Wu, Z., & Yu, J. (2018) · Cited by 4

Video object detection algorithm based on dynamic combination of sparse feature propagation and dense feature aggregation

Cao, D., Ma, J., & Chen, Z. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09827-0 · Cited by 4

Video Object Detection Using Motion Context and Feature Aggregation

Kim, J., Koh, J., & Choi, J. W. (2020) · International Conference on Information and Communication Technology Convergence (ICTC) · doi:10.1109/ictc49870.2020.9289386 · Cited by 4

Multi-object Tracking with a Hierarchical Single-Branch Network

Wang, F., Luo, L., Zhu, E., & Wang, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-98355-0_7 · Cited by 4

A novel memory mechanism for video object detection from indoor mobile robots

Hu, J., Wang, T., Li, Y., & Zhu, S. (2021) · Signal Image and Video Processing · doi:10.1007/s11760-021-01926-1 · Cited by 4

Simple Online Unmanned Aerial Vehicle Tracking with Transformer

Liu, Y., Wang, E., Song, X., Wang, Z., Liu, M., & Shu, W. (2021) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom53373.2021.00168 · Cited by 4

Deep learning for pedestrian behavior understanding

Gazzeh, S., & Douik, A. (2022) · International Conference on Advanced Technologies for Signal and Image Processing · doi:10.1109/atsip55956.2022.9805916 · Cited by 4

Improved Feature Extraction and Similarity Algorithm for Video Object Detection

You, H., Lu, Y., & Tang, H. (2023) · Information · doi:10.3390/info14020115 · Cited by 4

SwinVid: Enhancing Video Object Detection Using Swin Transformer

Maharek, A., Abozeid, A., Orban, R., & ElDahshan, K. A. (2024) · Computer Systems Science and Engineering · doi:10.32604/csse.2024.039436 · Cited by 4

Key-Track: A Lightweight Scalable LSTM-based Pedestrian Tracker for Surveillance Systems

Kulkarni, P., Mohan, S., Rogers, S., & Tabkhi, H. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-27272-2_18 · Cited by 4

Object detection in the police surveillance scenario

Wilkowski, A., Kasprzak, W., & Stefańczyk, M. (2019) · Annals of Computer Science and Information Systems · doi:10.15439/2019f291 · Cited by 4

New access services in HbbTV based on a deep learning approach for media content analysis

Uribe, S., Belmonte-Hernández, A., Moreno, F., Llorente, Á., López, J. P., & Álvarez, F. (2019) · Artificial intelligence for engineering design analysis and manufacturing · doi:10.1017/s0890060419000350 · Cited by 4

MTCNN-KCF-deepSORT:Driver Face Detection and Tracking Algorithm Based on Cascaded Kernel Correlation Filtering and Deep SORT

Liao, J., Wang, Q., Cao, L., Xia, J., & Zhang, Y. (2020) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2020-01-1038 · Cited by 4

Automated repair of fragmented tracks with 1D CNNs

Rana, M. S., Nibali, A., He, Z., & Morgan, S. (2020) · Image and Vision Computing · doi:10.1016/j.imavis.2020.103982 · Cited by 4

Anchor-Free One-Stage Online Multi-object Tracking

Zhou, Z., Li, Y., Gao, J. G., Xing, J., Li, L., & Hu, W. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60639-8_5 · Cited by 4

Learning intra-inter semantic aggregation for video object detection

Liang, J. S., Chen, H., Du, K., Yan, Y., & Wang, H. (2021) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3444685.3446273 · Cited by 4

Pedestrian Tracking through Coordinated Mining of Multiple Moving Cameras

Zhang, Y., & Wang, Q. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00033 · Cited by 4

Human Detection in Aerial Images using Deep Learning Techniques

Gundu, S., Syed, H., & Harikiran, J. (2022) · International Conference on Artificial Intelligence and Signal Processing (AISP) · doi:10.1109/aisp53593.2022.9760635 · Cited by 4

Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos

Hwang, S., Heo, M., Oh, S. W., & Kim, S. J. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01654 · Cited by 4

Finding a Needle in a Haystack: Tiny Flying Object Detection in 4K Videos using a Joint Detection-and-Tracking ApproachPreprint

Yoshihashi, R., Kawakami, R., You, S., Trinh, T. T., Iida, M., & Naemura, T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.08253 · Cited by 5

Pose-Based Isolated Sign Language Recognition with Semantic Mapping and CorrFormer

Wang, G., Wang, B., Zhai, H., Tao, Q., Jing, S., & Jin, P. (2025) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd64889.2025.11033397 · Cited by 3

Paying attention to other animal detections improves camera trap classification models

Dussert, G., Dray, S., Chamaillé‐Jammes, S., & Miele, V. (2026) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.70260 · Cited by 3

One-Stage Anchor-Free Online Multiple Target Tracking With Deformable Local Attention and Task-Aware Prediction

Hu, W., Wang, S., Zhou, Z., Gao, J. G., Li, Y., & Maybank, S. J. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3457886 · Cited by 3

Weighted Kernel Filter Based Anti-Air Object Tracking for Thermal Infrared Systems

Kim, C., & Ko, H. (2020) · Sensors · doi:10.3390/s20154081 · Cited by 3

Online Pedestrian Multiple-Object Tracking with Prediction Refinement and Track Classification

Yang, J., Ge, H., Yang, J., Tong, Y., & Su, S. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-10840-7 · Cited by 3

TMTB: Transformer based multi-task branching multi-object tracking algorithm for wide-view scenes

Li, H., & Li, J. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-17255-z · Cited by 3

Counterfactual contrastive learning for weakly supervised temporal sentence grounding

Xu, Y., Xu, W., & Miao, Z. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.129508 · Cited by 3

Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection

Koh, J., Kim, J., Shin, Y., Lee, B., Yang, S., & Choi, J. W. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9561778 · Cited by 3

Associative affinity network learning for multi-object tracking

Ma, L., Zhong, Q., Zhang, Y., Xie, D., & Pu, S. (2021) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.2000272 · Cited by 3

Multi-view aggregation for real-time accurate object detection of a moving camera

Hu, J., Wang, T., & Zhu, S. (2022) · Journal of Real-Time Image Processing · doi:10.1007/s11554-022-01253-9 · Cited by 3

Real-time Multiple Objects Following Using a UAV

Liu, J., & Yao, Y. (2023) · AIAA SciTech Forum · doi:10.2514/6.2023-1143 · Cited by 3

A Fast Unified System for 3D Object Detection and Tracking

Heitzinger, T., & Kampel, M. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01563 · Cited by 3

Video Object Detection by Aggregating Features across Adjacent Frames

Zhang, R., Miao, Z., Zhang, Q., Hao, S., & Wang, S. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1229/1/012039 · Cited by 3

D2T: A Framework For transferring detection to tracking

Qin, H., Yu, C., Gao, C., & Sang, N. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108544 · Cited by 3

Methodological Insights Towards Leveraging Performance in Video Object Tracking and Detection

Divyaprabha, D., & Kurian, M. Z. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140851 · Cited by 3

Object-aware Feature Aggregation for Video Object DetectionPreprint

Geng, Q., Zhang, H., Jiang, N., Qi, X., Zhang, L., & Zhou, Z. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.12573 · Cited by 3

VideoClick: Video Object Segmentation with a Single ClickPreprint

Homayounfar, N., Liang, J., Ma, W.-C., & Urtasun, R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2101.06545 · Cited by 3

Learning to Track Object Position through OcclusionPreprint

Chakraborty, S., & Hebert, M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.10766 · Cited by 3

FLSTrack: focused linear attention swin-transformer network with dual-branch decoder for end-to-end multi-object tracking

Zu, D., Duan, X., Kong, G., & Long, H. (2024) · Signal Image and Video Processing · doi:10.1007/s11760-024-03676-2 · Cited by 3

Generalizing Reuse Patterns for Efficient DNN on Microcontrollers

Liu, J., Ren, B., & Shen, X. (2025) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/3676641.3716257 · Cited by 2

Enhanced Global Context Fusion for Multi-Target Multi-Camera Tracking in the Bird's Eye View

Hu, S., Yang, C., Pang, X., Liu, S., Song, A., & Wang, H. (2025) · International Conference on Robotics and Control Engineering (RobCE) · doi:10.1145/3733774.3735327 · Cited by 2

Boosting Single-Domain Generalized Object Detection via Vision-Language Knowledge Interaction

Xu, X., Yang, J., Chong, W., Shi, W., Sun, S., Xing, J., & Liu, J. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3754870 · Cited by 2

RadarTracker: An End-to-End Transformer Framework for Vessel Tracking Using X-Band Marine Radar

Wang, Z., Li, X., Tian, C., Xia, L., Zhu, W., & Peng, Y.-L. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3628899 · Cited by 2

Video semantics exploration for indexing and retrieval

(2020) · Al-Azhar Bulletin of Science · doi:10.21608/absb.2020.210373 · Cited by 2

SAMF-TLD Based Pedestrian Multi-Target Tracking

Liu, B., Zhao, Y., Yang, H., & Cao, L. (2023) · International Conference on Computer Engineering and Application (ICCEA) · doi:10.1109/iccea58433.2023.10135431 · Cited by 2

Enhancing Forest Security through Advanced Surveillance Applications

Buchman, D., Krilavičius, T., & Maskeliūnas, R. (2023) · Forests · doi:10.3390/f14122335 · Cited by 2

An Effective Method for Semi-Online Multi-Object Tracking Refinement

Wang, M., Liu, R., Lina, S., Abe, N., & Yamada, S. (2024) · IEEE Access · doi:10.1109/access.2024.3394534 · Cited by 2

TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentation

Zhou, J., Mei, J., Wu, P., Chen, L., Zhao, F., Zhao, X., & Hu, Y. H. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10801543 · Cited by 2

Multi-Modal Integration of 2D and 3D Attributes for Multi-Vehicles Tracking

Altaf, M. A., & Kim, M. Y. (2024) · International Conference on Information and Communication Technology Convergence (ICTC) · doi:10.1109/ictc62082.2024.10827704 · Cited by 2

Optimized Yolov5s Algorithm for Enhanced Autonomous Driving Obstacle Detection

Chen, E., Guan, J., Wu, Y., & Li, H. (2024) · International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE) · doi:10.1109/cbase64041.2024.10824247 · Cited by 2

Enhancing Embodied Object Detection with Spatial Feature Memory

Chapman, N. H., Lehnert, C., Browne, W. N., & Dayoub, F. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00673 · Cited by 2

Performance of object recognition in wearable videos

Sabater, A., Montesano, L., & Murillo, A. C. (2019) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2019.8869019 · Cited by 2

Improved Traffic Sign Detection In Videos Through Reasoning Effective RoI Proposals

Zhang, Y., Qi, Y., Yang, J., & Hwang, J. (2020) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme46284.2020.9102896 · Cited by 2

VMM: Viewpoint-based Memory Mechanism for Object Detection of Moving Sensors

Hu, J., Wang, T., & Zhu, S. (2022) · International Conference on Intelligent Systems and Computer Vision (ISCV) · doi:10.1109/iscv54655.2022.9806119 · Cited by 2

TemporalNet: Real-time 2D-3D Video Object Detection

Chen, M., & Lang, J. (2022) · Canadian Conference on Computer and Robot Vision · doi:10.1109/crv55824.2022.00034 · Cited by 2

Even-Order Taylor Approximation-Based Feature Refinement and Dynamic Aggregation Model for Video Object Detection

Chen, L., Li, J., Li, Y., & Zhao, Q. (2023) · Electronics · doi:10.3390/electronics12204305 · Cited by 2

A literature review on the detection and tracking of obstacles applied for Advanced Driver Assistance Systems (ADAS) in Robotic Vehicle

Bruno, D. R., & Osório, F. S. (2023) · Latin American Robotics Symposium, Brazilian Symposium on Robotics and Workshop on Robotics in Education (LARS/SBR/WRE) · doi:10.1109/lars/sbr/wre59448.2023.10332971 · Cited by 2

MTD: Multi-Timestep Detector for Delayed Streaming Perception

Huang, Y., & Chen, N. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-8435-0_27 · Cited by 4

Self-supervised re-identification for online joint multi-object tracking

Li, S., Yang, L., Tan, H., Wang, B., Huang, W., Liu, H., Yang, W., & Lan, L. (2024) · Knowledge and Information Systems · doi:10.1007/s10115-024-02237-w · Cited by 2

Representation alignment contrastive regularisation for multi‐object tracking

Chen, S., Liu, Z., Dong, J., Wang, X., & Zhou, D. (2024) · IET Computer Vision · doi:10.1049/cvi2.12331 · Cited by 2

Feature Aligned Recurrent Network for Causal Video Object Detection

Wang, Y., Li, D., Lin, L., Chen, B., Wang, L., & Zhang, M. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803638 · Cited by 2

MART: Motion-Aware Recurrent Neural Network for Robust Visual Tracking

Fan, H., & Ling, H. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00061 · Cited by 3

Video Object Detection Using Event-Aware Convolutional Lstm and Object Relation Networks

Zhang, C. G., Xia, Z., & Kim, J. (2021) · Electronics · doi:10.3390/electronics10161918 · Cited by 3

A Novel Approach for Object Detection using Integrated Approach

Sunitha, T., & Devi, G. L. (2022) · International Conference on Electronics and Renewable Systems (ICEARS) · doi:10.1109/icears53579.2022.9752373 · Cited by 2

P-IoU: Accurate Motion Prediction Based Data Association for Multi-object Tracking

Wu, X., & Xu, J. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-8073-4_37 · Cited by 2

Accurate Single-Stream Action Detection in Real-Time

Liu, Y., Yang, F., & Dominique Ginhac, B. (2019) · International Conference on Distributed Smart Cameras · doi:10.1145/3349801.3349821 · Cited by 2

Rethinking Temporal Object Detection from Robotic Perspectives

Yu, J., Chen, X., & Kong, S. (2021) · CRC Press eBooks · doi:10.1201/9781003144281-5 · Cited by 2

End-to-End Multiple Object Tracking with Siamese Networks

Qin, J., Huang, C., & Xu, J. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-92310-5_65 · Cited by 2

Long Term Temporal Context for Per-Camera Object DetectionPreprint

Beery, S., Wu, G., Rathod, V., Votel, R., & Huang, J. (2019) · arXiv (Cornell University) · Cited by 2

Robust Instance Tracking via Uncertainty FlowPreprint

Qian, J., Nan, J., Ancha, S., Okorn, B., & Held, D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.04367 · Cited by 2

Localization-Based TrackingPreprint

Gloudemans, D., & Work, D. B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.05823 · Cited by 2

Temporal Early Exits for Efficient Video Object DetectionPreprint

Sabet, A., Hare, J. S., Al‐Hashimi, B. M., & Merrett, G. V. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4001358 · Cited by 2

Mapping urban large‐area advertising structures using drone imagery and deep learning‐based spatial data analysis

Ptak, B., & Kraft, M. (2024) · Transactions in GIS · doi:10.1111/tgis.13208 · Cited by 1

A proposal-level class-aware graph convolutional network and memory bank for thyroid nodule detection in ultrasound videos

Duan, Z., Li, Y., & Luo, H. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107206 · Cited by 1

CTTrack: Leveraging Cross-Transformer for Multi-Scale Feature Fusion in Multi-Object Tracking

Zhang, Z., Cao, C., & Zheng, F. (2024) · International Conference on Computers and Artificial Intelligence Technology (CAIT) · doi:10.1109/cait64506.2024.10963082 · Cited by 1

Real-Batch: Real-Time Adaptive Batch Processing for Accurate Object Detection in Autonomous Driving

Liu, T., Wang, S., Li, B., Dong, Z., Wang, G., Gong, W., & He, T. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3625072 · Cited by 1

GridTrack: Detection and Tracking of Multiple Objects in Dynamic Occupancy Grids

Erkent, Ö., González, D., Paigwar, A., & Laugier, C. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87156-7_15 · Cited by 1

Flexible Temporal Correlation Learning for Human, Animal, and Interactor Detection in Videos

Feng, Y., & Liu, J. (2025) · Sensors and Materials · doi:10.18494/sam4423 · Cited by 1

Autoregressive Temporal Modeling for Advanced Tracking-by-Diffusion

Nguyen, P., Madhok, R., Raj, B., & Luu, K. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-025-02439-x · Cited by 1

Real-time rodent behavior classifier using color-based body segmentation (R2C2)

Jo, J., Park, T., Hwang, S., Lee, S., Min, J., Park, G., Song, M., Kwag, J., Kim, H., Lee, C., et al. (2025) · Lab Animal · doi:10.1038/s41684-025-01634-0 · Cited by 1

High Performance Autonomous Target Tracking and Control Method for Quadrotors Using Artificial Intelligence

Han, T. T., Duy, A. L., Van, T. N., Tan, H. D., & Trung, A. D. (2025) · IEEE Access · doi:10.1109/access.2025.3640672 · Cited by 1

Object Detection from Video Tubelets with Convolutional Neural Networks

Kang, K., Ouyang, W., Li, H., & Wang, X. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.95 · Cited by 386

Analyzing the Performance of Object Detection and Tracking Techniques

Chavan, S. A., Chaudhari, N. M., & Ramteke, R. J. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-16-9967-2_44 · Cited by 1

Object Tracking in Videos Using CNN

Singh, U., Saini, A., & Domala, R. (2020) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-1420-3_55 · Cited by 2

Spatio-temporal object detection by deep learning: Video-interlacing to improve multi-object tracking

Mhalla, A., Château, T., & Amara, N. E. B. (2019) · Image and Vision Computing · doi:10.1016/j.imavis.2019.03.002 · Cited by 32

Tracking Assisted Faster Video Object Detection

Yang, W., Liu, B., Li, W., & Yu, N. (2019) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2019.00301 · Cited by 13