Large Motion Model for Unified Multi-Modal Motion Generation

no code implementations • 1 Apr 2024 • Mingyuan Zhang, Daisheng Jin, Chenyang Gu, Fangzhou Hong, Zhongang Cai, Jingfang Huang, Chongzhi Zhang, Xinying Guo, Lei Yang, Ying He, Ziwei Liu

In this work, we present Large Motion Model (LMM), a motion-centric, multi-modal framework that unifies mainstream motion generation tasks into a generalist model.

Robust Geometry and Reflectance Disentanglement for 3D Face Reconstruction from Sparse-view Images

no code implementations • 11 Dec 2023 • Daisheng Jin, Jiangbei Hu, Baixin Xu, Yuxin Dai, Chen Qian, Ying He

This paper presents a novel two-stage approach for reconstructing human faces from sparse-view images, a task made challenging by the unique geometry and complex skin reflectance of each individual.

3D Face Reconstruction Disentanglement +1

Delving Deep into the Generalization of Vision Transformers under Distribution Shifts

1 code implementation • CVPR 2022 • Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, Ziwei Liu

By comprehensively investigating these GE-ViTs and comparing with their corresponding CNN models, we observe: 1) For the enhanced model, larger ViTs still benefit more for the OOD generalization.

Out-of-Distribution Generalization Self-Supervised Learning

Towards Overcoming False Positives in Visual Relationship Detection

no code implementations • 23 Dec 2020 • Daisheng Jin, Xiao Ma, Chongzhi Zhang, Yizhuo Zhou, Jiashu Tao, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, Zhoujun Li, Xianglong Liu, Hongsheng Li

We observe that during training, the relationship proposal distribution is highly imbalanced: most of the negative relationship proposals are easy to identify, e. g., the inaccurate object detection, which leads to the under-fitting of low-frequency difficult proposals.

Graph Attention Human-Object Interaction Detection +4