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Amodal Instance Segmentation via Prior-Guided Expansion

Chen, J., Niu, L., Zhang, J., Si, J., Qian, C., & Zhang, L. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i1.25104 · Cited by 16 · see citing works

Toward explainable artificial intelligence: A survey and overview on their intrinsic properties

Mi, J., Jiang, X., Luo, L., & Gao, Y. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126919 · Cited by 18 · see citing works

Integrative review of data sciences for driving smart mobility in intelligent transportation systems

Jalil, K., Xia, Y., Chen, Q., Zahid, M. N., Manzoor, T., & Zhao, J. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109624 · Cited by 13 · see citing works

Occluded Text Detection and Recognition in the Wild

Raisi, Z., & Zelek, J. (2022) · Canadian Conference on Computer and Robot Vision · doi:10.1109/crv55824.2022.00026 · Cited by 13 · see citing works

OccRob: Efficient SMT-Based Occlusion Robustness Verification of Deep Neural Networks

Guo, X., Zhou, Z., Zhang, Y., Katz, G., & Zhang, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-30823-9_11 · Cited by 13 · see citing works

NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose EstimationPreprint

Wang, A., Kortylewski, A., & Yuille, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2101.12378 · Cited by 13 · see citing works

Adversarial Patch Attacks and Defences in Vision-Based Tasks: A SurveyPreprint

Sharma, A., Bian, Y., Munz, P., & Narayan, A. (2022) · doi:10.36227/techrxiv.20085902 · Cited by 13 · see citing works

MVDet: multi-view multi-class object detection without ground plane assumption

Park, S., Yang, S., & Lee, H.-J. (2023) · Pattern Analysis and Applications · doi:10.1007/s10044-023-01168-6 · Cited by 10 · see citing works

Peeking into the unseen: Occlusion-resistant segmentation for preweaning piglets under crushing events

Gan, H., Menegon, F., Sun, A., Scollo, A., Jiang, Q., Xue, Y., & Norton, T. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.108683 · Cited by 10 · see citing works

BLADE: Box-Level Supervised Amodal Segmentation through Directed Expansion

Liu, Z., Li, Z., & Jiang, T. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i4.28176 · Cited by 10 · see citing works

OOD-CV-v2 : An Extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

Zhao, B., Wang, J., Ma, W., Jesslen, A., Yang, S., Yu, S., Zendel, O., Theobalt, C., Yuille, A., & Kortylewski, A. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3462293 · Cited by 9 · see citing works

A Convolutional Neural-Network-Based Training Model to Estimate Actual Distance of Persons in Continuous Images

Tsai, Y., Modales, A. V., & Lin, H.-T. (2022) · Sensors · doi:10.3390/s22155743 · Cited by 8 · see citing works

Occlusion Problem in 3D Object Detection: A Review

Kandelkar, A., Batra, I., Sharma, S., & Malik, A. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-19-2821-5_26 · Cited by 8 · see citing works

Towards Efficient Foundation Model for Zero-shot Amodal Segmentation

Liu, Z., Qiao, L., Chu, X., Ma, L., & Jiang, T. (2025) · 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/cvpr52734.2025.01886 · Cited by 7 · see citing works

Cofopose: Conditional 2D Pose Estimation with Transformers

Aidoo, E., Wang, X., Liu, Z., Tenagyei, E. K., Owusu-Agyemang, K., Kodjiku, S. L., Ejianya, V. N., & Aggrey, E. S. E. B. (2022) · Sensors · doi:10.3390/s22186821 · Cited by 7 · see citing works

Advancements in collision avoidance techniques for internet-connected vehicles: A comprehensive review of methods and challenges

Jalil, K., Xia, Y., & Zhao, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111836 · Cited by 6 · see citing works

A Bayesian Approach to OOD Robustness in Image Classification

Kaushik, P., Kortylewski, A., & Yuille, A. (2024) · 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/cvpr52733.2024.02169 · Cited by 6 · see citing works

Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions

Wu, R., Cheng, K., Shen, Y., Ning, C., Zhan, G., & Dong, H. (2023) · arXiv · doi:10.48550/arxiv.2309.07510 · Cited by 11 · see citing works

Shape Feature Extraction Techniques for Computer Vision Applications

Raj, E. F. I., & Balaji, M. (2023) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-031-20541-5_4 · Cited by 5 · see citing works

Knowledge-Aware Neuron Interpretation for Scene Classification

Guan, Y., Lécué, F., Chen, J., Li, R., & Pan, J. Z. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i3.27965 · Cited by 5 · see citing works

Blocks World Revisited: The Effect of Self-Occlusion on Classification by Convolutional Neural Networks

Solbach, M. D., & Tsotsos, J. K. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00390 · Cited by 5 · see citing works

A Light-Weight Interpretable Model for Nuclei Detection and Weakly-Supervised Segmentation

Zhang, Y., Kortylewski, A., Liu, Q., Park, S., Green, B., Engle, E. L., Almodovar, G., Walk, R., Soto-Diaz, S., Taube, J. M., et al. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16961-8_15 · Cited by 5 · see citing works

Voiced Subordinate for Visually Impaired in record maintenance with Proximal Object Recognition and Voice Assistant Framework

Sajini, S., & Pushpa, B. (2023) · International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) · doi:10.1109/icaect57570.2023.10117829 · Cited by 4 · see citing works

Compositional Generative Networks and Robustness to Perceptible Image Changes

Kortylewski, A., He, J., Liu, Q., Cosgrove, C., Yang, C., & Yuille, A. (2021) · Conference on Information Sciences and Systems · doi:10.1109/ciss50987.2021.9400221 · Cited by 4 · see citing works

A depth information aided real-time instance segmentation method for space task scenarios under CPU platform

Li, Q., Zhu, Z., Liang, J., Zhang, H., Xu, Y., & Zhang, Z. (2023) · Acta Astronautica · doi:10.1016/j.actaastro.2023.01.007 · Cited by 4 · see citing works

Analysis of the Matchability of Reference Imagery for Aircraft Based on Regional Scene Perception

Li, X., Guo Zhang, A., Cui, H., Ma, J., & Wang, W. (2023) · Remote Sensing · doi:10.3390/rs15174353 · Cited by 4 · see citing works

Understanding the role of pathways in a deep neural network

Lyu, L., Pang, C., & Wang, J. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106095 · Cited by 4 · see citing works

Neural Textured Deformable Meshes for Robust Analysis-by-Synthesis

Wang, A., Ma, W., Yuille, A., & Kortylewski, A. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00308 · Cited by 4 · see citing works

A progressive framework for rotary motion deblurring

Qin, J., Ma, Y., Huang, J., Fan, F., & Du, Y. (2023) · Defence Technology · doi:10.1016/j.dt.2023.04.007 · Cited by 3 · see citing works

Latent Enhancing Autoencoder for Occluded Image Classification

Kotwal, K., Deshmukh, T., & Gopal, P. (2024) · Proceedings - International Conference on Image Processing · doi:10.1109/icip51287.2024.10647790 · Cited by 3 · see citing works

COCO-OLAC: A Benchmark for Occluded Panoptic Segmentation and Image Understanding

Wei, W., Wang, J., & Bhalerao, A. H. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890039 · Cited by 3 · see citing works

HB-net: Holistic bursting cell cluster integrated network for occluded multi-objects recognition

Gao, X., Gao, X., Rong, J., Chen, X., Liao, X., & Chen, J. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130071 · Cited by 3 · see citing works

Amodal Segmentation for Laparoscopic Surgery Video Instruments

Shi, R., Liu, Z., Duan, L., & Jiang, T. (2025) · Sensing and Imaging · doi:10.1007/s11220-025-00609-2 · Cited by 3 · see citing works

From a Visual Scene to a Virtual Representation: A Cross-Domain Review

Pereira, A., Carvalho, P., Pereira, N., Viana, P., & Côrte-Real, L. (2023) · IEEE Access · doi:10.1109/access.2023.3283495 · Cited by 4 · see citing works

Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch AttacksPreprint

Cosgrove, C., Kortylewski, A., Yang, C., & Yuille, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.00558 · Cited by 3 · see citing works

COMPAS: Representation Learning with Compositional Part Sharing for Few-Shot Classification.Preprint

He, J., Kortylewski, A., & Yuille, A. (2021) · arXiv (Cornell University) · Cited by 3 · see citing works

Indian TSR for partial occlusion using GDNN

Sanyal, B., Mohapatra, R., & Dash, R. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16168-1 · Cited by 2 · see citing works

Self-Supervised Occlusion Detection and Avoidance using Differentiable Rendering

Szántó, M., & Szemenyei, M. (2022) · International Symposium on Measurement and Control in Robotics (ISMCR) · doi:10.1109/ismcr56534.2022.9950574 · Cited by 2 · see citing works

Improving Multimodal Object Detection with Individual Sensor Monitoring

Kuhn, C. B., Hofbauer, M., Ma, B., Petrović, G., & Steinbach, E. G. (2022) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism55400.2022.00022 · Cited by 2 · see citing works

Analysis of Frequency Range Effect on the Detection of Voice Disorder Using Convolutional Neural Networks Trained on Spectogram Images

Paulino, J. A. S., Gomes, H. M., Batista, L. V., & Lopes, L. W. (2024) · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) · doi:10.1109/sibgrapi62404.2024.10716317 · Cited by 1 · see citing works

DiL: An Explainable and Practical Metric for Abnormal Uncertainty in Object Detection

Giloni, A., Hofman, O., Morikawa, I., Shimizu, T., Elovici, Y., & Shabtai, A. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00249 · Cited by 1 · see citing works

Scaling 3D Compositional Models for Robust Classification and Pose Estimation

Yuan, X., Zhang, G., Kaushik, P., Jesslen, A., Kortylewski, A., & Yuille, A. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00604 · Cited by 1 · see citing works

A Systematic Review of Explainable Convolutional Neural Networks for Image Classification

Hasić, V., & Krivić, S. (2026) · Expert Systems · doi:10.1111/exsy.70279 · Cited by 1 · see citing works

Online learning of positive and negative prototypes with explanations based on kernel expansion

Esmaeli, H., Ghiasi-Shirazi, K., & Harati, A. (2022) · Journal of Iranian Association of Electrical and Electronics Engineers · doi:10.52547/jiaeee.20.1.67 · Cited by 1 · see citing works

Occlusion Avoidance in a Simulated Environment Using Reinforcement Learning

Szemenyei, M., & Szántó, M. (2023) · Applied Sciences · doi:10.3390/app13053090 · Cited by 1 · see citing works

A Novel Approach for Recognizing Occluded Objects Using Feature Pyramid Network Based on Occlusion Rate Analysis

Ouardirhi, Z., Mahmoudi, S. A., & Zbakh, M. (2023) · International Conference on Cloud Computing Technologies and Applications (CloudTech) · doi:10.1109/cloudtech58737.2023.10366103 · Cited by 1 · see citing works

NeRF-YOLO: Detecting Occluded Objects via Multi-view Geometric Aggregation

Szemenyei, M., & Kőfaragó, N. (2024) · Mechanisms and machine science · doi:10.1007/978-3-031-51085-4_2 · Cited by 1 · see citing works

Robust Instance Segmentation through Reasoning about Multi-Object OcclusionPreprint

Yuan, X., Kortylewski, A., Sun, Y., & Yuille, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.02107 · Cited by 1 · see citing works

A Light-weight Interpretable CompositionalNetwork for Nuclei Detection and Weakly-supervised SegmentationPreprint

Zhang, Y., Kortylewski, A., Liu, Q., Park, S., Green, B., Engle, E. L., Almodovar, G., Walk, R., Soto-Diaz, S., Taube, J. M., et al. (2021) · arXiv (Cornell University) · Cited by 1 · see citing works

Occlusion Scene Classification via Cascade Supervised Contrastive LearningPreprint

xu, J. (2022) · doi:10.36227/techrxiv.20794765.v1 · Cited by 1 · see citing works

Interesting Receptive Region and Feature Excitation for Partial Person Re-identification

Meng, Q., Li, T., Ji, S., Zhu, S., & Gu, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86380-7_24

ROBIN : A Benchmark for Robustness to Individual Nuisancesin Real-World Out-of-Distribution ShiftsPreprint

Zhao, B., Yu, S., Ma, W., Yu, M., Mei, S., Wang, A., He, J., Yuille, A., & Kortylewski, A. (2021) · arXiv (Cornell University)

A Finite-Time Speed and Direction Control for Four-Wheel Drive System

Shareef, S. J. M., & Aula, F. T. (2021) · UKH Journal of Science and Engineering · doi:10.25079/ukhjse.v5n2y2021.pp47-55

Co-attention Network for Visual Question Answering Based on Dual Attention

Dong, F., Wang, X., Oad, A., & Talpur, M. S. H. (2021) · Journal of Engineering Science and Technology Review · doi:10.25103/jestr.146.13

Occlusion Scene Classification via Cascade Supervised Contrastive LearningPreprint

xu, J. (2022) · doi:10.36227/techrxiv.20794765

Recognition of Occluded Goods under Prior Inference Based on Generative Adversarial Network

Cao, M., Xie, K., Liu, F., Li, B., Wen, C. B., He, J., & Zhang, W. (2023) · Sensors · doi:10.3390/s23063355

Multi-Scale Compositional Constraints for Representation Learning on Videos

Paraskevopoulos, G., Lavania, C., Chum, L., & Sundaram, S. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10096573

Hb-Net: Holistic Bursting Cell Cluster Integrated Network for Occluded Multi-Objects RecognitionPreprint

Gao, X., Gao, X., Rong, J., Chen, X., Liao, X., & Chen, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4620490

BYNet: A Bayesian Approach for Robust Palmprint and Palm Vein Recognition

Xian, T., Xu, H., Wang, J., & Ubul, K. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-5628-1_14

eAodeMar: a lightweight and real-time occluded marine vessel detection network for embedded marine platforms

Wang, Y., Wang, M., Shi, J., Ni, Z., & Li, G. (2026) · Frontiers in Marine Science · doi:10.3389/fmars.2026.1778827

Motion and Spatiotemporal Aggregation Network for Occlusion Edge Detection From Videos

Chen, L., Pu, M., Zhihao, L. I. U., Hou, X., Huang, Y., Zhou, R., & Ling, H. (2026) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2026.3673936

Development of an automated fruit classification system by using computer vision and deep learning

Mac, T. T., Bui, H., Pham, D.-V., Ly, H.-H., & Nguyen, X. (2026) · HardwareX · doi:10.1016/j.ohx.2026.e00775

Assessing the Impacts of Canopy Structure on Aerial Sensor PerformancePreprint

Hodgdon, T., West, B. A., Breton, D. J., & Niccolai, A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6667610

DS-DETR: adaptive counting algorithm for high-density rebar areas

Zhang, S., Du, Y., Deng, J., & Xu, H. (2026) · Measurement Science and Technology · doi:10.1088/1361-6501/ae7589

OCC-MLLM-V1: Occlusion reasoning with commonsense-guided Multi-modal LLM based agent via internal Chain-of-Thoughts (CoTs)

Wang, C., He, Q., Pei, J., Xia, L., Liu, J., Li, B., & Di, X. (2026) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2026.104828

Assessing Occlusion Robustness in Binarized Neural Networks

Zuhra, A., Dutta, S., & Prasad, S. (2026) · International Journal of Approximate Reasoning · doi:10.1016/j.ijar.2026.109786

MOSAIC: Maximizing out-of-distribution sensitivity via aligned image classification

Madni, H. A., Umer, R. M., Marr, C., & Foresti, G. L. (2026) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2026.104885

Cascaded Deraining-Enhanced Fruit Detection for All-Weather Orchard Environments

Wang, M., Li, J., Wang, L., & Shi, G. (2026) · International Conference on Image, Vision and Computing (ICIVC) · doi:10.1109/icivc70586.2026.11686743

HIDA: A Human-Intuition-Guided Depth-Aware Framework for Zero-Shot Amodal Segmentation

Li, P., Wang, K., Chen, B., Hou, Y.-L., Shen, M., & Li, B. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37531-5_35

Prototype-contrastive learning with visibility-guided distractor absorption for occlusion-robust recognition

Zhang, X., Chen, Y., Cang, Y., Ning, Z., & Shi, L. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.135287

Dataset's Occlusion Levels Selection Based on Shannon Entropy in the Feature Space

Николаевич, С. В., & Mouromtsev, D. I. (2026) · International Russian Automation Conference (RusAutoCon) · doi:10.1109/rusautocon69876.2026.11707479

Sinusoidal Position Encodings Adapted to the Two-Dimensional Spatial Domain for Occluded Objects Detection

Николаевич, С. В., & Mouromtsev, D. I. (2026) · International Russian Automation Conference (RusAutoCon) · doi:10.1109/rusautocon69876.2026.11707474

Compositional Convolutional Neural Networks: A Deep Architecture With Innate Robustness to Partial Occlusion

Kortylewski, A., He, J., Liu, Q., & Yuille, A. (2020) · 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/cvpr42600.2020.00896 · Cited by 107 · see citing works

Compositional Convolutional Networks For Robust Object Classification under Occlusion.Preprint

Kortylewski, A., Liu, Q., Wang, H., Zhang, Z., & Yuille, A. (2019) · arXiv (Cornell University) · Cited by 4 · see citing works

Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion

Kortylewski, A., Liu, Q., Wang, H., Zhang, Z., & Yuille, A. (2020) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv45572.2020.9093560 · Cited by 68 · see citing works

Robust Object Detection Under Occlusion With Context-Aware CompositionalNets

Wang, A., Sun, Y., Kortylewski, A., & Yuille, A. (2020) · 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/cvpr42600.2020.01266 · Cited by 142 · see citing works

Localizing Occluders with Compositional Convolutional Networks

Kortylewski, A., Liu, Q., Wang, H., Zhang, Z., & Yuille, A. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00253 · Cited by 3 · see citing works