2 citations · 3 across the 12 of their papers we have counts for
13 papers
Interpolation of subspaces of infinite codimension
Corentin Audiard
Given three normed spaces , with a closed subspace of with same norm, how does compare to $[X\_0 , X\_1 ]\_θ\,…
Implicit Drifting Policy: One-Step Action Generation via Conditional Expert Geometry
Zemin Yang, Yaoyu He, Yiming Zhong +5
Generative action policies based on diffusion or flow matching excel in behavior cloning, yet their iterative sampling is prohibitive for high-frequency robot control. While recent…
From Noise to Intent: Anchoring Generative VLA Policies with Residual Bridges
Yiming Zhong, Yaoyu He, Zemin Yang +5
Bridging high-level semantic understanding with low-level physical control remains a persistent challenge in embodied intelligence, stemming from the fundamental spatiotemporal sca…
Controllable Video Object Insertion via Multi-View Priors
Qi Xia, Peishan Cong, Yichen Yao +3
Video object insertion places a user-specified object in an existing dynamic scene. Existing methods typically condition generation on text or a single reference image. Consequentl…
Driving Like Yourself: A Benchmark for Closed-Loop Personalized End-to-End Autonomous Driving
Xiaoru Dong, Ruiqin Li, Xiao Han +7
Human driving behavior is inherently diverse, yet most end-to-end autonomous driving (E2E-AD) systems learn a single average driving style, neglecting individual differences. Achie…
MoE3D: Mixture of Experts meets Multi-Modal 3D Understanding
Yu Li, Yuenan Hou, Yingmei Wei +4
Multi-modal 3D understanding is a fundamental task in computer vision. Previous multi-modal fusion methods typically employ a single, dense fusion network, struggling to handle the…
ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving
Yuhang Lu, Jiadong Tu, Yuexin Ma +1
End-to-end autonomous driving has emerged as a promising approach to unify perception, prediction, and planning within a single framework, reducing information loss and improving a…
STAGE: A Stream-Centric Generative World Model for Long-Horizon Driving-Scene Simulation
Jiamin Wang, Yichen Yao, Xiang Feng +5
The generation of temporally consistent, high-fidelity driving videos over extended horizons presents a fundamental challenge in autonomous driving world modeling. Existing approac…
HUMOF: Human Motion Forecasting in Interactive Social Scenes
Caiyi Sun, Yujing Sun, Xiao Han +5
Complex scenes present significant challenges for predicting human behaviour due to the abundance of interaction information, such as human-human and humanenvironment interactions.…
FreeCap: Hybrid Calibration-Free Motion Capture in Open Environments
Aoru Xue, Yiming Ren, Zining Song +3
We propose a novel hybrid calibration-free method FreeCap to accurately capture global multi-person motions in open environments. Our system combines a single LiDAR with expandable…
Towards Practical Human Motion Prediction with LiDAR Point Clouds
Xiao Han, Yiming Ren, Yichen Yao +2
Human motion prediction is crucial for human-centric multimedia understanding and interacting. Current methods typically rely on ground truth human poses as observed input, which i…
Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving
Yuhang Lu, Yichen Yao, Jiadong Tu +3
Large Vision-Language Models (LVLMs) have recently garnered significant attention, with many efforts aimed at harnessing their general knowledge to enhance the interpretability and…
RenderWorld: World Model with Self-Supervised 3D Label
Ziyang Yan, Wenzhen Dong, Yihua Shao +8
End-to-end autonomous driving with vision-only is not only more cost-effective compared to LiDAR-vision fusion but also more reliable than traditional methods. To achieve a economi…