6 papers
PriGo: Test-Time Primitive Guidance to Diffusion and Flow Policies for Adaptive Robotic Manipulation
Zezeng Li, Enda Xiang, Thuy Tran +3
Imitation learning has enabled remarkable progress in robotic manipulation, especially with diffusion and flow-based policies that generate complex visuomotor behaviors directly fr…
ADPro: a Test-time Adaptive Diffusion Policy via Manifold-constrained Denoising and Task-aware Initialization for Robotic Manipulation
Zezeng Li, Rui Yang, Ruochen Chen +2
Diffusion policies have recently emerged as a powerful class of visuomotor controllers for robot manipulation, offering stable training and expressive multi-modal action modeling.…
Robotic Manipulation via Imitation Learning: Taxonomy, Evolution, Benchmark, and Challenges
Zezeng Li, Alexandre Chapin, Enda Xiang +6
Robotic Manipulation (RM) is central to the advancement of autonomous robots, enabling them to interact with and manipulate objects in real-world environments. This survey focuses…
HOTS3D: Hyper-Spherical Optimal Transport for Semantic Alignment of Text-to-3D Generation
Zezeng Li, Weimin Wang, Yuming Zhao +3
Recent CLIP-guided 3D generation methods have achieved promising results but struggle with generating faithful 3D shapes that conform with input text due to the gap between text an…
NoPain: No-box Point Cloud Attack via Optimal Transport Singular Boundary
Zezeng Li, Xiaoyu Du, Na Lei +2
Adversarial attacks exploit the vulnerability of deep models against adversarial samples. Existing point cloud attackers are tailored to specific models, iteratively optimizing per…
Point2Quad: Generating Quad Meshes from Point Clouds via Face Prediction
Zezeng Li, Zhihui Qi, Weimin Wang +3
Quad meshes are essential in geometric modeling and computational mechanics. Although learning-based methods for triangle mesh demonstrate considerable advancements, quad mesh gene…