Dai, Jifeng

Deformable Convolutional Networks

Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., & Wei, Y. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 7,513

Deformable DETR: Deformable Transformers for End-to-End Object Detection

Zhu, X., Su, W., Lu, L., Li, B., Wang, X., & Dai, J. (2020) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 6,027

Deformable ConvNets V2: More Deformable, Better Results

Zhu, X., Hu, H., Lin, S., & Dai, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2,943

MMDetection: Open MMLab Detection Toolbox and Benchmark

Chen, K., Wang, J., Pang, J., Cao, Y., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Xu, J., et al. (2019) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2,227

Relation Networks for Object Detection

Hu, H., Gu, J., Zhang, Z., Dai, J., & Wei, Y. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,524

BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Yu, Q., & Dai, J. (2022) · arXiv

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 1,419

Instance-aware Semantic Segmentation via Multi-task Network Cascades

Dai, J., He, K., & Sun, J. (2015) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,273

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation

Lin, D., Dai, J., Jia, J., He, K., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 1,129

Fully Convolutional Instance-Aware Semantic Segmentation

Li, Y., Qi, H., Dai, J., Ji, X., & Wei, Y. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,116

InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

Wang, W., Dai, J., Chen, Z., Huang, Z., Li, Z., Zhu, X., Hu, X., Lu, T., Lu, L., Li, H., et al. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,080

VL-BERT: Pre-training of Generic Visual-Linguistic Representations

Su, W., Zhu, X., Cao, Y., Li, B., Lu, L., Wei, F., & Dai, J. (2019) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 950

Flow-Guided Feature Aggregation for Video Object Detection

Zhu, X., Wang, Y., Dai, J., Yuan, L., & Wei, Y. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 729

An Empirical Study of Spatial Attention Mechanisms in Deep Networks

Zhu, X., Cheng, D., Zhang, Z., Lin, S., & Dai, J. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 659

Exploring Cross-Image Pixel Contrast for Semantic Segmentation

Wang, W., Zhou, T., Yu, F., Dai, J., Konukoglu, E., & Gool, L. V. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 604

Frozen CLIP Models are Efficient Video Learners

Lin, Z., Geng, S., Zhang, R., Gao, P., de Melo, G., Wang, X., Dai, J., Qiao, Y., & Li, H. (2022) · Lecture Notes in Computer Science

Human Pose and Action RecognitionMultimodal Machine Learning Applications

Cited by 213

Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory

Zhu, X., Chen, Y., Tian, H., Tao, C., Su, W., Yang, C., Huang, G., Li, B., Lu, L., Wang, X., et al. (2023) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 33

RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis

Mu, Y., Chen, J., Zhang, Q., Chen, S., Yu, Q., Ge, C., Chen, R., Liang, Z., Hu, M., Tao, C., et al. (2024) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 3