activity
20182024
most citedVisual Transformers: Token-based Image Representation and Processing for Computer Vision

380 citations · 923 across the 38 of their papers we have counts for

collaborators

39 papers

cs.CV2024★ 3 cited

Cache Me if You Can: Accelerating Diffusion Models through Block Caching

Felix Wimbauer, Bichen Wu, Edgar Schoenfeld +11

Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the major drawbacks of diffusion…

cs.CV2023★ 2 cited

FlowVid: Taming Imperfect Optical Flows for Consistent Video-to-Video Synthesis

Feng Liang, Bichen Wu, Jialiang Wang +8

Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampere…

cs.CV2023★ 1 cited

Fairy: Fast Parallelized Instruction-Guided Video-to-Video Synthesis

Bichen Wu, Ching-Yao Chuang, Xiaoyan Wang +6

In this paper, we introduce Fairy, a minimalist yet robust adaptation of image-editing diffusion models, enhancing them for video editing applications. Our approach centers on the…

cs.CV2023

ControlRoom3D: Room Generation using Semantic Proxy Rooms

Jonas Schult, Sam Tsai, Lukas Höllein +11

Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by genera…

cs.CV2023

MixRT: Mixed Neural Representations For Real-Time NeRF Rendering

Chaojian Li, Bichen Wu, Peter Vajda +1

Neural Radiance Field (NeRF) has emerged as a leading technique for novel view synthesis, owing to its impressive photorealistic reconstruction and rendering capability. Neverthele…

cs.CV2023★ 1 cited

AVID: Any-Length Video Inpainting with Diffusion Model

Zhixing Zhang, Bichen Wu, Xiaoyan Wang +6

Recent advances in diffusion models have successfully enabled text-guided image inpainting. While it seems straightforward to extend such editing capability into the video domain,…