110 citations · 249 across the 21 of their papers we have counts for
23 papers
AvatarGO: Zero-shot 4D Human-Object Interaction Generation and Animation
Yukang Cao, Liang Pan, Kai Han +2
Recent advancements in diffusion models have led to significant improvements in the generation and animation of 4D full-body human-object interactions (HOI). Nevertheless, existing…
GS-VTON: Controllable 3D Virtual Try-on with Gaussian Splatting
Yukang Cao, Masoud Hadi, Liang Pan +1
Diffusion-based 2D virtual try-on (VTON) techniques have recently demonstrated strong performance, while the development of 3D VTON has largely lagged behind. Despite recent advanc…
Exploiting Hierarchical Interactions for Protein Surface Learning
Yiqun Lin, Liang Pan, Yi Li +2
Predicting interactions between proteins is one of the most important yet challenging problems in structural bioinformatics. Intrinsically, potential function sites in protein surf…
Large-Vocabulary 3D Diffusion Model with Transformer
Ziang Cao, Fangzhou Hong, Tong Wu +2
Creating diverse and high-quality 3D assets with an automatic generative model is highly desirable. Despite extensive efforts on 3D generation, most existing works focus on the gen…
PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds
Zhongang Cai, Liang Pan, Chen Wei +6
Human pose and shape estimation (HPS) has attracted increasing attention in recent years. While most existing studies focus on HPS from 2D images or videos with inherent depth ambi…
Towards Real-World Visual Tracking with Temporal Contexts
Ziang Cao, Ziyuan Huang, Liang Pan +3
Visual tracking has made significant improvements in the past few decades. Most existing state-of-the-art trackers 1) merely aim for performance in ideal conditions while overlooki…
HumanLiff: Layer-wise 3D Human Generation with Diffusion Model
Shoukang Hu, Fangzhou Hong, Tao Hu +5
3D human generation from 2D images has achieved remarkable progress through the synergistic utilization of neural rendering and generative models. Existing 3D human generative mode…
Temporally-Adaptive Models for Efficient Video Understanding
Ziyuan Huang, Shiwei Zhang, Liang Pan +4
Spatial convolutions are extensively used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in diffe…
Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
Youquan Liu, Lingdong Kong, Jun Cen +5
Recent advancements in vision foundation models (VFMs) have opened up new possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a novel fram…
DiffMimic: Efficient Motion Mimicking with Differentiable Physics
Jiawei Ren, Cunjun Yu, Siwei Chen +3
Motion mimicking is a foundational task in physics-based character animation. However, most existing motion mimicking methods are built upon reinforcement learning (RL) and suffer…
Variational Relational Point Completion Network for Robust 3D Classification
Liang Pan, Xinyi Chen, Zhongang Cai +4
Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise, which hampers 3D geometric modeling and perception. Existing point cloud completion methods t…
RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions
Shaoyuan Xie, Lingdong Kong, Wenwei Zhang +4
The recent advances in camera-based bird's eye view (BEV) representation exhibit great potential for in-vehicle 3D perception. Despite the substantial progress achieved on standard…
ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model
Mingyuan Zhang, Xinying Guo, Liang Pan +5
3D human motion generation is crucial for creative industry. Recent advances rely on generative models with domain knowledge for text-driven motion generation, leading to substanti…
Robo3D: Towards Robust and Reliable 3D Perception against Corruptions
Lingdong Kong, Youquan Liu, Xin Li +6
The robustness of 3D perception systems under natural corruptions from environments and sensors is pivotal for safety-critical applications. Existing large-scale 3D perception data…
SHERF: Generalizable Human NeRF from a Single Image
Shoukang Hu, Fangzhou Hong, Liang Pan +3
Existing Human NeRF methods for reconstructing 3D humans typically rely on multiple 2D images from multi-view cameras or monocular videos captured from fixed camera views. However,…
BiBench: Benchmarking and Analyzing Network Binarization
Haotong Qin, Mingyuan Zhang, Yifu Ding +5
Network binarization emerges as one of the most promising compression approaches offering extraordinary computation and memory savings by minimizing the bit-width. However, recent…
OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation
Tong Wu, Jiarui Zhang, Xiao Fu +9
Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale realscanned 3D databases. To facilitate the development of 3D perception, re…
EVA3D: Compositional 3D Human Generation from 2D Image Collections
Fangzhou Hong, Zhaoxi Chen, Yushi Lan +2
Inverse graphics aims to recover 3D models from 2D observations. Utilizing differentiable rendering, recent 3D-aware generative models have shown impressive results of rigid object…
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
Mingyuan Zhang, Zhongang Cai, Liang Pan +4
Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent moti…
Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer
Zhipeng Luo, Changqing Zhou, Liang Pan +6
With the prevalence of LiDAR sensors in autonomous driving, 3D object tracking has received increasing attention. In a point cloud sequence, 3D object tracking aims to predict the…
LaserMix for Semi-Supervised LiDAR Semantic Segmentation
Lingdong Kong, Jiawei Ren, Liang Pan +1
Densely annotating LiDAR point clouds is costly, which restrains the scalability of fully-supervised learning methods. In this work, we study the underexplored semi-supervised lear…
AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars
Fangzhou Hong, Mingyuan Zhang, Liang Pan +3
3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technolog…
LiDAR-based 4D Panoptic Segmentation via Dynamic Shifting Network
Fangzhou Hong, Hui Zhou, Xinge Zhu +2
With the rapid advances of autonomous driving, it becomes critical to equip its sensing system with more holistic 3D perception. However, existing works focus on parsing either the…