no code implementations • 3 Feb 2025 • Shaoting Zhu, Linzhan Mou, Derun Li, Baijun Ye, Runhan Huang, Hang Zhao
Recent success in legged robot locomotion is attributed to the integration of reinforcement learning and physical simulators.
no code implementations • 11 Sep 2024 • Shaoting Zhu, Runhan Huang, Linzhan Mou, Hang Zhao
In this work, we propose a novel approach that enables quadruped robots to pass various small obstacles, or "tiny traps".
no code implementations • 10 Jul 2024 • Yili Liu, Linzhan Mou, Xuan Yu, Chenrui Han, Sitong Mao, Rong Xiong, Yue Wang
Accurate perception of the dynamic environment is a fundamental task for autonomous driving and robot systems.
no code implementations • CVPR 2024 • Linzhan Mou, Jun-Kun Chen, Yu-Xiong Wang
This paper proposes Instruct 4D-to-4D that achieves 4D awareness and spatial-temporal consistency for 2D diffusion models to generate high-quality instruction-guided dynamic scene editing results.
1 code implementation • 3 Jun 2024 • Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying WEI
In this paper, we introduce DuQuant, a novel approach that utilizes rotation and permutation transformations to more effectively mitigate both massive and normal outliers.
no code implementations • CVPR 2024 • Zhen Xu, Sida Peng, Chen Geng, Linzhan Mou, Zihan Yan, Jiaming Sun, Hujun Bao, Xiaowei Zhou
Based on the HDQ algorithm, we leverage sphere tracing to efficiently estimate the surface intersection and light visibility.
no code implementations • CVPR 2023 • Shangzhan Zhang, Sida Peng, Tianrun Chen, Linzhan Mou, Haotong Lin, Kaicheng Yu, Yiyi Liao, Xiaowei Zhou
We introduce a novel approach that takes a single semantic mask as input to synthesize multi-view consistent color images of natural scenes, trained with a collection of single images from the Internet.