49 citations · 116 across the 20 of their papers we have counts for
14 papers · 1 filter
ShowRoom3D: Text to High-Quality 3D Room Generation Using 3D Priors
Weijia Mao, Yan-Pei Cao, Jia-Wei Liu +2
We introduce ShowRoom3D, a three-stage approach for generating high-quality 3D room-scale scenes from texts. Previous methods using 2D diffusion priors to optimize neural radiance…
VideoSwap: Customized Video Subject Swapping with Interactive Semantic Point Correspondence
Yuchao Gu, Yipin Zhou, Bichen Wu +7
Current diffusion-based video editing primarily focuses on structure-preserved editing by utilizing various dense correspondences to ensure temporal consistency and motion alignmen…
X-Adapter: Adding Universal Compatibility of Plugins for Upgraded Diffusion Model
Lingmin Ran, Xiaodong Cun, Jia-Wei Liu +5
We introduce X-Adapter, a universal upgrader to enable the pretrained plug-and-play modules (e.g., ControlNet, LoRA) to work directly with the upgraded text-to-image diffusion mode…
ColonNeRF: High-Fidelity Neural Reconstruction of Long Colonoscopy
Yufei Shi, Beijia Lu, Jia-Wei Liu +2
Colonoscopy reconstruction is pivotal for diagnosing colorectal cancer. However, accurate long-sequence colonoscopy reconstruction faces three major challenges: (1) dissimilarity a…
DeformGS: Scene Flow in Highly Deformable Scenes for Deformable Object Manipulation
Bardienus P. Duisterhof, Zhao Mandi, Yunchao Yao +8
Teaching robots to fold, drape, or reposition deformable objects such as cloth will unlock a variety of automation applications. While remarkable progress has been made for rigid o…
MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model
Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew +5
This paper studies the human image animation task, which aims to generate a video of a certain reference identity following a particular motion sequence. Existing animation works t…
Revisiting the Domain Shift and Sample Uncertainty in Multi-source Active Domain Transfer
Wenqiao Zhang, Zheqi Lv, Hao Zhou +5
Active Domain Adaptation (ADA) aims to maximally boost model adaptation in a new target domain by actively selecting a limited number of target data to annotate.This setting neglec…
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…
Instant3D: Instant Text-to-3D Generation
Ming Li, Pan Zhou, Jia-Wei Liu +4
Text-to-3D generation has attracted much attention from the computer vision community. Existing methods mainly optimize a neural field from scratch for each text prompt, relying on…
MotionDirector: Motion Customization of Text-to-Video Diffusion Models
Rui Zhao, Yuchao Gu, Jay Zhangjie Wu +5
Large-scale pre-trained diffusion models have exhibited remarkable capabilities in diverse video generations. Given a set of video clips of the same motion concept, the task of Mot…
DynVideo-E: Harnessing Dynamic NeRF for Large-Scale Motion- and View-Change Human-Centric Video Editing
Jia-Wei Liu, Yan-Pei Cao, Jay Zhangjie Wu +6
Despite recent progress in diffusion-based video editing, existing methods are limited to short-length videos due to the contradiction between long-range consistency and frame-wise…
Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation
David Junhao Zhang, Jay Zhangjie Wu, Jia-Wei Liu +5
Significant advancements have been achieved in the realm of large-scale pre-trained text-to-video Diffusion Models (VDMs). However, previous methods either rely solely on pixel-bas…
HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video
Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang +5
We introduce HOSNeRF, a novel 360° free-viewpoint rendering method that reconstructs neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild video…
STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition
Ming Li, Xiangyu Xu, Hehe Fan +7
Existing methods of privacy-preserving action recognition (PPAR) mainly focus on frame-level (spatial) privacy removal through 2D CNNs. Unfortunately, they have two major drawbacks…