| Task2sim: Towards effective pre-training and transfer from synthetic data S Mishra, R Panda, CP Phoo, CFR Chen, L Karlinsky, K Saenko, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 65 | 2022 |
| Incremental object learning from contiguous views S Stojanov, S Mishra, NA Thai, N Dhanda, A Humayun, C Yu, LB Smith, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 58 | 2019 |
| How Transferable are Video Representations Based on Synthetic Data? Y Kim, S Mishra, SY Jin, R Panda, H Kuenhe, L Karlinsky, V Saligrama, ... Advances in Neural Information Processing Systems, 2022 | 52 | 2022 |
| Surprisingly simple semi-supervised domain adaptation with pretraining and consistency S Mishra, K Saenko, V Saligrama British Machine Vision Conference (BMVC), 2021 | 39 | 2021 |
| Self-supervised visual attribute learning for fashion compatibility D Kim, K Saito, S Mishra, S Sclaroff, K Saenko, BA Plummer Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 32 | 2021 |
| Visda-2021 competition: Universal domain adaptation to improve performance on out-of-distribution data D Bashkirova, D Hendrycks, D Kim, H Liao, S Mishra, C Rajagopalan, ... NeurIPS 2021 Competitions and Demonstrations Track, 66-79, 2022 | 29 | 2022 |
| Effectively leveraging attributes for visual similarity S Mishra, Z Zhang, Y Shen, R Kumar, V Saligrama, BA Plummer Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 15 | 2021 |
| VisDA 2022 challenge: Domain adaptation for industrial waste sorting D Bashkirova, S Mishra, D Lteif, P Teterwak, D Kim, F Alladkani, J Akl, ... NeurIPS 2022 Competition Track, 104-118, 2023 | 10 | 2023 |
| Learning human action recognition representations without real humans H Zhong, S Mishra, D Kim, SY Jin, R Panda, H Kuehne, L Karlinsky, ... Advances in Neural Information Processing Systems 36, 65069-65087, 2023 | 9 | 2023 |
| Interpretable compositional representations for robust few-shot generalization S Mishra, P Zhu, V Saligrama IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (3), 1496-1512, 2022 | 6* | 2022 |
| Low dimensional visual attributes: An interpretable image encoding P Zhu, R Zhu, S Mishra, V Saligrama International Conference on Pattern Recognition, 90-102, 2021 | 4 | 2021 |
| Faster algorithms for weighted recursive state machines K Chatterjee, B Kragl, S Mishra, A Pavlogiannis European Symposium on Programming, 287-313, 2017 | 4 | 2017 |
| SCRAMBLe: Enhancing Multimodal LLM Compositionality with Synthetic Preference Data S Mishra, K Saenko, V Saligrama Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2025 | 2* | 2025 |
| SPARC: Score Prompting and Adaptive Fusion for Zero-Shot Multi-Label Recognition in Vision-Language Models K Miller, A Gangrade, S Mishra, K Saenko, V Saligrama Proceedings of the Computer Vision and Pattern Recognition Conference, 4313-4321, 2025 | 2 | 2025 |
| Fine-grained few-shot recognition by deep object parsing R Zhu, P Zhu, S Mishra, V Saligrama arXiv preprint arXiv:2207.07110, 2022 | 2 | 2022 |
| Syncdr: Training cross domain retrieval models with synthetic data S Mishra, CD Castillo, H Wang, K Saenko, V Saligrama arXiv preprint arXiv:2401.00420, 2023 | 1 | 2023 |
| Robust Dictionary Learning for Image Processing S Mishra Indian Institute of Technology, Bombay, 0 | | |
Venkatesh SaligramaAI Professor and Amazon ScholarVerified email at bu.edu
