21 citations · 56 across the 23 of their papers we have counts for
24 papers
FlowHMR: Physically Plausible Motion Capture from Video
Zhanke Wang, Chengfeng Zhao, Qing Shuai +8
We present FlowHMR, a framework for recovering physically plausible global 3D human motion from monocular video. Previous learning-based methods typically regress human motion dire…
AnimateCanvas: Learning Implicit Motion Planning from Composable Kinematic Cues
Zeyu Ling, Di Kang, Qing Shuai +7
Professional character animation requires both natural motion and precise, versatile control. For example, creators often define the timing of a specified action, control the motio…
GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking
Zeyu Ling, Xinyao Yu, Renye Yan +4
General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to extend. Text-to-motion generator…
AnyAct: Towards Human Reenactment of Character Motion From Video
Liuhan Chen, Lei Zhong, Jiawei Wang +5
We study the problem of directly deriving an initial human reenactment from a monocular video of a non-human character. Our goal is not to reconstruct the source character itself b…
PRISM: Streaming Human Motion Generation with Per-Joint Latent Decomposition
Zeyu Ling, Qing Shuai, Teng Zhang +3
Text-to-motion generation has advanced with larger corpora and stronger generators, yet many models still rely on holistic frame- or clip-level latents that entangle trajectory, or…
CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos
Chengfeng Zhao, Jiazhi Shu, Yubo Zhao +7
In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistenc…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…
Ready-to-React: Online Reaction Policy for Two-Character Interaction Generation
Zhi Cen, Huaijin Pi, Sida Peng +5
This paper addresses the task of generating two-character online interactions. Previously, two main settings existed for two-character interaction generation: (1) generating one's…
IDOL: Instant Photorealistic 3D Human Creation from a Single Image
Yiyu Zhuang, Jiaxi Lv, Hao Wen +7
Creating a high-fidelity, animatable 3D full-body avatar from a single image is a challenging task due to the diverse appearance and poses of humans and the limited availability of…
Motion-2-To-3: Leveraging 2D Motion Data for 3D Motion Generations
Ruoxi Guo, Huaijin Pi, Zehong Shen +8
Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods often rely on 3D motion capture da…
AnchorCrafter: Animate Cyber-Anchors Selling Your Products via Human-Object Interacting Video Generation
Ziyi Xu, Ziyao Huang, Juan Cao +7
The generation of anchor-style product promotion videos presents promising opportunities in e-commerce, advertising, and consumer engagement. Despite advancements in pose-guided hu…
Reconstructing Close Human Interactions from Multiple Views
Qing Shuai, Zhiyuan Yu, Zhize Zhou +4
This paper addresses the challenging task of reconstructing the poses of multiple individuals engaged in close interactions, captured by multiple calibrated cameras. The difficulty…
AniDress: Animatable Loose-Dressed Avatar from Sparse Views Using Garment Rigging Model
Beijia Chen, Yuefan Shen, Qing Shuai +3
Recent communities have seen significant progress in building photo-realistic animatable avatars from sparse multi-view videos. However, current workflows struggle to render realis…
EasyVolcap: Accelerating Neural Volumetric Video Research
Zhen Xu, Tao Xie, Sida Peng +7
Volumetric video is a technology that digitally records dynamic events such as artistic performances, sporting events, and remote conversations. When acquired, such volumography ca…
Dyn-E: Local Appearance Editing of Dynamic Neural Radiance Fields
Shangzan Zhang, Sida Peng, Yinji ShenTu +5
Recently, the editing of neural radiance fields (NeRFs) has gained considerable attention, but most prior works focus on static scenes while research on the appearance editing of d…
Learning Human Mesh Recovery in 3D Scenes
Zehong Shen, Zhi Cen, Sida Peng +3
We present a novel method for recovering the absolute pose and shape of a human in a pre-scanned scene given a single image. Unlike previous methods that perform sceneaware mesh op…
Representing Volumetric Videos as Dynamic MLP Maps
Sida Peng, Yunzhi Yan, Qing Shuai +2
This paper introduces a novel representation of volumetric videos for real-time view synthesis of dynamic scenes. Recent advances in neural scene representations demonstrate their…
Reconstructing Hand-Held Objects from Monocular Video
Di Huang, Xiaopeng Ji, Xingyi He +5
This paper presents an approach that reconstructs a hand-held object from a monocular video. In contrast to many recent methods that directly predict object geometry by a trained n…
Animatable Implicit Neural Representations for Creating Realistic Avatars from Videos
Sida Peng, Zhen Xu, Junting Dong +5
This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene i…
Efficient Neural Radiance Fields for Interactive Free-viewpoint Video
Haotong Lin, Sida Peng, Zhen Xu +4
This paper aims to tackle the challenge of efficiently producing interactive free-viewpoint videos. Some recent works equip neural radiance fields with image encoders, enabling the…
Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies
Sida Peng, Junting Dong, Qianqian Wang +4
This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene i…
Reconstructing 3D Human Pose by Watching Humans in the Mirror
Qi Fang, Qing Shuai, Junting Dong +2
In this paper, we introduce the new task of reconstructing 3D human pose from a single image in which we can see the person and the person's image through a mirror. Compared to gen…
Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans
Sida Peng, Yuanqing Zhang, Yinghao Xu +4
This paper addresses the challenge of novel view synthesis for a human performer from a very sparse set of camera views. Some recent works have shown that learning implicit neural…
Motion Capture from Internet Videos
Junting Dong, Qing Shuai, Yuanqing Zhang +3
Recent advances in image-based human pose estimation make it possible to capture 3D human motion from a single RGB video. However, the inherent depth ambiguity and self-occlusion i…