33 citations · 38 across the 15 of their papers we have counts for
17 papers
Autoregressive B-Rep Shape Generation with Parametric Surfaces
Dafei Qin, Rui Xu, Zeyu Shen +8
Generative CAD modeling has broad design and application potential. Despite significant advances in Boundary Representation (B-Rep) generation, the dominant representation in CAD,…
Contact Matrix: Enhancing Dance Motion Synthesis with Precise Interaction Modeling
Xuhai Chen, Zhi Cen, Huaijin Pi +3
Generating realistic reactive motions, in which one person reacts to the fixed motions of others, is challenging due to strict interaction constraints and a limited feasible soluti…
Strips as Tokens: Artist Mesh Generation with Native UV Segmentation
Rui Xu, Dafei Qin, Kaichun Qiao +8
Recent advancements in autoregressive transformers have demonstrated remarkable potential for generating artist-quality meshes. However, the token ordering strategies employed by e…
EmbodMocap: In-the-Wild 4D Human-Scene Reconstruction for Embodied Agents
Wenjia Wang, Liang Pan, Huaijin Pi +8
Human behaviors in the real world naturally encode rich, long-term contextual information that can be leveraged to train embodied agents for perception, understanding, and acting.…
Gloria: Consistent Character Video Generation via Content Anchors
Yuhang Yang, Fan Zhang, Huaijin Pi +5
Digital characters are central to modern media, yet generating character videos with long-duration, consistent multi-view appearance and expressive identity remains challenging. Ex…
CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects
Huaijin Pi, Zhi Cen, Zhiyang Dou +1
Synthesizing whole-body manipulation of articulated objects, including body motion, hand motion, and object motion, is a critical yet challenging task with broad applications in vi…
MotionStreamer: Streaming Motion Generation via Diffusion-based Autoregressive Model in Causal Latent Space
Lixing Xiao, Shunlin Lu, Huaijin Pi +7
This paper addresses the challenge of text-conditioned streaming motion generation, which requires us to predict the next-step human pose based on variable-length historical motion…
Mocap-2-to-3: Multi-view Lifting for Monocular Motion Recovery with 2D Pretraining
Zhumei Wang, Zechen Hu, Ruoxi Guo +5
Human motion recovery for real-world interaction demands both precise action details and metric-scale trajectories. Recovering absolute human pose from monocular input presents a 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…
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…
World-Grounded Human Motion Recovery via Gravity-View Coordinates
Zehong Shen, Huaijin Pi, Yan Xia +6
We present a novel method for recovering world-grounded human motion from monocular video. The main challenge lies in the ambiguity of defining the world coordinate system, which v…
Generating Human Motion in 3D Scenes from Text Descriptions
Zhi Cen, Huaijin Pi, Sida Peng +5
Generating human motions from textual descriptions has gained growing research interest due to its wide range of applications. However, only a few works consider human-scene intera…
Hierarchical Generation of Human-Object Interactions with Diffusion Probabilistic Models
Huaijin Pi, Sida Peng, Minghui Yang +2
This paper presents a novel approach to generating the 3D motion of a human interacting with a target object, with a focus on solving the challenge of synthesizing long-range and d…
A Joint Modeling of Vision-Language-Action for Target-oriented Grasping in Clutter
Kechun Xu, Shuqi Zhao, Zhongxiang Zhou +4
We focus on the task of language-conditioned grasping in clutter, in which a robot is supposed to grasp the target object based on a language instruction. Previous works separately…
E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context
Zizhang Li, Mengmeng Wang, Huaijin Pi +3
Recently, the image-wise implicit neural representation of videos, NeRV, has gained popularity for its promising results and swift speed compared to regular pixel-wise implicit rep…
Searching for TrioNet: Combining Convolution with Local and Global Self-Attention
Huaijin Pi, Huiyu Wang, Yingwei Li +2
Recently, self-attention operators have shown superior performance as a stand-alone building block for vision models. However, existing self-attention models are often hand-designe…
Deep Snake for Real-Time Instance Segmentation
Sida Peng, Wen Jiang, Huaijin Pi +3
This paper introduces a novel contour-based approach named deep snake for real-time instance segmentation. Unlike some recent methods that directly regress the coordinates of the o…