32 citations · 44 across the 22 of their papers we have counts for
6 papers · 1 filter
GenDeF: Learning Generative Deformation Field for Video Generation
Wen Wang, Kecheng Zheng, Qiuyu Wang +5
We offer a new perspective on approaching the task of video generation. Instead of directly synthesizing a sequence of frames, we propose to render a video by warping one static im…
AutoStory: Generating Diverse Storytelling Images with Minimal Human Effort
Wen Wang, Canyu Zhao, Hao Chen +3
Story visualization aims to generate a series of images that match the story described in texts, and it requires the generated images to satisfy high quality, alignment with the te…
De novo protein design using geometric vector field networks
Weian Mao, Muzhi Zhu, Zheng Sun +4
Innovations like protein diffusion have enabled significant progress in de novo protein design, which is a vital topic in life science. These methods typically depend on protein st…
Object-aware Inversion and Reassembly for Image Editing
Zhen Yang, Ganggui Ding, Wen Wang +3
By comparing the original and target prompts, we can obtain numerous editing pairs, each comprising an object and its corresponding editing target. To allow editability while maint…
RGM: A Robust Generalizable Matching Model
Songyan Zhang, Xinyu Sun, Hao Chen +2
Finding corresponding pixels within a pair of images is a fundamental computer vision task with various applications. Due to the specific requirements of different tasks like optic…
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
Weijia Wu, Yuzhong Zhao, Hao Chen +6
Current deep networks are very data-hungry and benefit from training on largescale datasets, which are often time-consuming to collect and annotate. By contrast, synthetic data can…