About Me
Greetings! I’m Jiamian Wang, a student at Golisano College of Computing and Information Sciences, Rochester Institute of Technology, under the guidance of Dr. Zhiqiang Tao. Prior to joining RIT, I spent one year in the Department of Computer Science and Engineering at Santa Clara University (San Jose, USA) with Dr.Tao. I received my M.S. degree from University of Southern California (Los Angeles, USA) in 2020 and B.E. degree from Tianjin University (Tianjin, China) in 2018.
My research primarily revolves around low-level vision tasks, such as image super-resolution. I am engaged in enhancing the trustworthiness, robustness, and performance of snapshot compressive imaging systems (SCI). My recent work delves into harnessing the power of diffusion models for both low-level vision tasks and high-level multi-modal retrieval task.
News
2024.10: [NeurIPS’24] I received NeurIPS’24 Travel Award. Thanks to NeurIPS and looking forward to visiting Vancouver!
2024.09: [NeurIPS’24] Two papers are accepted by NeurIPS 2024. One is FedHP, in which we developed a federated learning framework to effectively cooperate cross-silo computational imaging systems without breaking the privacy concern. One is about text-video retrieval, where we devised a diffusion-inspired iterative alignment process to solve for the multimodal modality gap and achieves encouraging performance. Code, pretrained models, and the manuscript will be released soon!
2024.09：I will server as a reviewer for AAAI 2025 and ICLR 2025.
2024.07: [ECCV’24] Our work of SQ-LLaVA has been accepted by ECCV 2024. Congratulations to Guohao!
2024.06: Poster, Video, and Supplementary Material has been released, looking forward to present our work in CVPR2024!
2024.05: I will serve as a reviewer for NeurIPS 2024.
2024.03: I will join Bosch Research and Technology Center as a research intern, focusing on autoregressive image generation, starting from May 2024.
2024.02: [CVPR’24] One paper on multi-modality text-video retrieval is accepted by CVPR 2024 as Highlight (11.9%). Check out the manuscript and the code.
2024.02: I will serve as a reviewer for ECCV 2024.
2023.11: I will serve as a reviewer for CVPR 2024.
2023.08: [ICCV’23] Code, including training, testing scripts, and pretrained models have been released. Check out Iterative-Soft-Shrinkage-SR for more details.
2023.07: [ICCV’23] One paper on efficient image super-resolution (Arxiv) is accepted by ICCV 2023. Looking forward to sharing our work in Paris.
2023.06: [Preprint] Check out our Federated learning method on snapshot compressive imaging, Federated Hardware-Prompt Learning (FedHP). This is the first attempt of discussing the power of FL in the field of SCI.
2023.03: [Preprint] Check out our new pruning method that flexibly handles diverse off-the-shelf SR network architectures without pre-training: Arxiv. Thanks to my co-authors’ great support.
2022.06. [ECCV’22] One paper on uncertainty quantification on SCI system is accpeted as an Oral paper by ECCV 2022 (2.7%). Check out the manuscript and the code.
Selected Publications and Preprints
 | Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval. Jiamian Wang, Guohao Sun, Pichao Wang, Dongfang Liu, Sohail Dianat, Majid Rabbani, Raghuveer Rao, Zhiqiang Tao. CVPR Highlight (11.9%), 2024.  Paper Code Video Supply Poster |
 | SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant. Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen, Ran Xu, Zhiqiang Tao. ECCV, 2024. Arxiv Code |
 | Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging. Jiamian Wang, Zongliang Wu, Yulun Zhang, Xin Yuan, Tao Lin, Zhiqiang Tao. NeurIPS, 2024. Arxiv |
 | Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution. Jiamian Wang, Huan Wang, Yulun Zhang, Yun Fu, Zhiqiang Tao. ICCV Poster (26.15%), 2023. Paper Code Supply Poster |
 | Modeling Mask Uncertainty in Hyperspectral Image Reconstruction. Jiamian Wang, Yulun Zhang, Xin Yuan, Ziyi Meng, Zhiqiang Tao. ECCV Oral (2.7%), 2022. Paper (Supply) Code Video Poster |
 | Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty. Xueying Yang, Jiamian Wang, Sheng Li, Zhiqiang Tao. CIKM, 2022. Paper Code |
 | S2-Transformer for Mask-Aware Hyperspectral Image Reconstruction. Jiamian Wang, Kunpeng Li, Yulun Zhang, Xin Yuan, Zhiqiang Tao. Arxiv, 2022. Arxiv Code |
 | A new backbone for hyperspectral image reconstruction. Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao. Arxiv, 2022. Arxiv Code |
Professional Services
- Journal Reviewer: TPAMI, PR, JSTSP, IJCV, TIP, TNNLS, TETCI, Neurocomputing.
- Conference Reviewer: NIPS2024, CVPR2024, ECCV2024, ICML2024, CIKM 2021-2023, ACM SIGKDD 2022-2023.