1 citations · 1 across the 7 of their papers we have counts for
8 papers
ELAN4D: Embodiment-Centric 4D Supervision for Vision-Language-Action Models via Plug-and-Play Adaptation
Zeyuan He, Bowen Yang, Zhirui Fang +9
Vision-Language-Action (VLA) models have shown promise for robotic manipulation, yet most existing policies operate reactively by directly regressing actions from current observati…
DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving
Chen Shi, Jinrui Xu, Shaoshuai Shi +3
Pretrained foundation models have become an important basis for end-to-end autonomous driving. In contrast to vision-language models pretrained primarily on static image-text pairs…
GeoPredict: Leveraging Predictive Kinematics and 3D Gaussian Geometry for Precise VLA Manipulation
Jingjing Qian, Boyao Han, Chen Shi +4
Vision-Language-Action (VLA) models achieve strong generalization in robotic manipulation but remain largely reactive and 2D-centric, making them unreliable in tasks that require p…
Enhancing Spatial Reasoning in Multimodal Large Language Models through Reasoning-based Segmentation
Zhenhua Ning, Zhuotao Tian, Shaoshuai Shi +4
Recent advances in point cloud perception have demonstrated remarkable progress in scene understanding through vision-language alignment leveraging large language models (LLMs). Ho…
Proteus-ID: ID-Consistent and Motion-Coherent Video Customization
Guiyu Zhang, Chen Shi, Zijian Jiang +4
Video identity customization seeks to synthesize realistic, temporally coherent videos of a specific subject, given a single reference image and a text prompt. This task presents t…
JiSAM: Alleviate Labeling Burden and Corner Case Problems in Autonomous Driving via Minimal Real-World Data
Runjian Chen, Wenqi Shao, Bo Zhang +3
Deep-learning-based autonomous driving (AD) perception introduces a promising picture for safe and environment-friendly transportation. However, the over-reliance on real labeled d…
AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Driving
Xiaosong Jia, Shaoshuai Shi, Zijun Chen +4
As an essential task in autonomous driving (AD), motion prediction aims to predict the future states of surround objects for navigation. One natural solution is to estimate the pos…
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Haiyang Wang, Hao Tang, Li Jiang +5
This paper proposes a simple, yet effective framework, called GiT, simultaneously applicable for various vision tasks only with a vanilla ViT. Motivated by the universality of the…