activity
20232026
most citedModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud Classification

2 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Superman: Unifying Skeleton and Vision for Human Motion Perception and Generation

Xinshun Wang, Peiming Li, Ziyi Wang +5

Human motion analysis tasks, such as temporal 3D pose estimation, motion prediction, and motion in-betweening, play an essential role in computer vision. However, current paradigms…

cs.CV2025

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning

Mengyuan Liu, Xinshun Wang, Zhongbin Fang +6

This paper aims to model 3D human motion across domains, where a single model is expected to handle multiple modalities, tasks, and datasets. Existing cross-domain models often rel…

cs.CV2025

Yan: Foundational Interactive Video Generation

Deheng Ye, Fangyun Zhou, Jiacheng Lv +15

We present Yan, a foundational framework for interactive video generation, covering the entire pipeline from simulation and generation to editing. Specifically, Yan comprises three…

cs.AI2024

Playable Game Generation

Mingyu Yang, Junyou Li, Zhongbin Fang +5

In recent years, Artificial Intelligence Generated Content (AIGC) has advanced from text-to-image generation to text-to-video and multimodal video synthesis. However, generating pl…

cs.CV2024

Point-In-Context: Understanding Point Cloud via In-Context Learning

Mengyuan Liu, Zhongbin Fang, Xia Li +4

The rise of large-scale models has catalyzed in-context learning as a powerful approach for multitasking, particularly in natural language and image processing. However, its applic…

cs.CV20242 cited

ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud Classification

Zhongbin Fang, Xia Li, Xiangtai Li +2

Recently, 3D point cloud classification has made significant progress with the help of many datasets. However, these datasets do not reflect the incomplete nature of real-world poi…