| Meta faster r-cnn: Towards accurate few-shot object detection with attentive feature alignment G Han, S Huang, J Ma, Y He, SF Chang Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 780-789, 2022 | 120 | 2022 |
| Few-shot object detection with fully cross-transformer G Han, J Ma, S Huang, L Chen, SF Chang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 105 | 2022 |
| Query adaptive few-shot object detection with heterogeneous graph convolutional networks G Han, Y He, S Huang, J Ma, SF Chang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 97 | 2021 |
| Task-adaptive negative envision for few-shot open-set recognition S Huang, J Ma, G Han, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 38 | 2022 |
| Supervised masked knowledge distillation for few-shot transformers H Lin, G Han, J Ma, S Huang, X Lin, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 19 | 2023 |
| Multi-Modal Few-Shot Object Detection with Meta-Learning-Based Cross-Modal Prompting G Han, L Chen, J Ma, S Huang, R Chellappa, SF Chang arXiv preprint arXiv:2204.07841, 2022 | 19 | 2022 |
| Digeo: Discriminative geometry-aware learning for generalized few-shot object detection J Ma, Y Niu, J Xu, S Huang, G Han, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 15 | 2023 |
| Towards fast adaptation of pretrained contrastive models for multi-channel video-language retrieval X Lin, S Tiwari, S Huang, M Li, MZ Shou, H Ji, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 15 | 2023 |
| Pyramid structured optical flow learning with motion cues J Dai, S Huang, T Nguyen 2018 25th IEEE international conference on image processing (ICIP), 3338-3342, 2018 | 12 | 2018 |
| Flow-distilled IP two-stream networks for compressed video action recognition S Huang, X Lin, S Karaman, SF Chang arXiv preprint arXiv:1912.04462, 2019 | 11 | 2019 |
| TempCLR: Temporal Alignment Representation with Contrastive Learning Y Yang, J Ma, S Huang, L Chen, X Lin, G Han, SF Chang The Eleventh International Conference on Learning Representations (ICLR), 2023 | 10 | 2023 |
| Few-shot end-to-end object detection via constantly concentrated encoding across heads J Ma, G Han, S Huang, Y Yang, SF Chang European Conference on Computer Vision, 57-73, 2022 | 10 | 2022 |
| Video in 10 bits: Few-bit videoqa for efficiency and privacy S Huang, R Piramuthu, SF Chang, GA Sigurdsson European Conference on Computer Vision, 738-754, 2022 | 2 | 2022 |
| Characterizing video question answering with sparsified inputs S Huang, R Piramuthu, V Ordonez, SF Chang, GA Sigurdsson arXiv preprint arXiv:2311.16311, 2023 | 1 | 2023 |
| A General Framework for Model Adaptation to Meet Practical Constraints in Computer Vision S Huang Columbia University, 2024 | | 2024 |
| Efficient evaluation of noncommutative polynomials using tensor and noncommutative Waring decompositions E Evert, JW Helton, S Huang, J Nie Numerical Functional Analysis and Optimization 42 (1), 39-68, 2020 | | 2020 |
| Wording Image for Domain-Invariant Representation in Domain Generalization J Ma, Y Niu, S Huang, G Han, SF Chang | | |
| Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval Supplementary Material XLS Tiwari, S Huang, M Li, MZ Shou, H Ji, SF Chang | | |
| Supplementary Materials for Few-Shot Object Detection with Fully Cross-Transformer G Han, J Ma, S Huang, L Chen, SF Chang | | |
| Supplementary Materials for Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks G Han, Y He, S Huang, J Ma, SF Chang | | |
Shih-Fu ChangProfessor of Electrical Engineering and Computer Science, Columbia UniversityEmail verificata su columbia.edu
