Jiamian Wang

Jiamian Wang

Rochester Institute of Technology, focus on Computer Vision, Machine Learning

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

Image 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.
Image Paper
Image Code
Image Video
Image Supply
Image Poster
Image SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant.
Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen, Ran Xu, Zhiqiang Tao.
ECCV, 2024.
Image Arxiv
Image Code
Image Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging.
Jiamian Wang, Zongliang Wu, Yulun Zhang, Xin Yuan, Tao Lin, Zhiqiang Tao.
NeurIPS, 2024.
Image Arxiv
Image Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution.
Jiamian Wang, Huan Wang, Yulun Zhang, Yun Fu, Zhiqiang Tao.
ICCV Poster (26.15%), 2023.
Image Paper
Image Code
Image Supply
Image Poster
Image Modeling Mask Uncertainty in Hyperspectral Image Reconstruction.
Jiamian Wang, Yulun Zhang, Xin Yuan, Ziyi Meng, Zhiqiang Tao.
ECCV Oral (2.7%), 2022.
Image Paper (Supply)
Image Code
Image Video
Image Poster
Image Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty.
Xueying Yang, Jiamian Wang, Sheng Li, Zhiqiang Tao.
CIKM, 2022.
Image Paper
Image Code
Image S2-Transformer for Mask-Aware Hyperspectral Image Reconstruction.
Jiamian Wang, Kunpeng Li, Yulun Zhang, Xin Yuan, Zhiqiang Tao.
Arxiv, 2022.
Image Arxiv
Image Code
Image A new backbone for hyperspectral image reconstruction.
Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao.
Arxiv, 2022.
Image Arxiv
Image 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.