7 papers
FastDSAC: Enhancing Policy Plasticity via Constrained Exploration for Scalable Humanoid Locomotion
Guanchen Lu, Yajuan Dun, Yi Zhou +4
Scalable reinforcement learning has popularized high-throughput sampling architectures, which significantly compresses the training time for off-policy methods in robotic locomotio…
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
Qi Lan, Yining Tang, Yu Shen +4
Safety-critical traffic scenario generation is essential for evaluating autonomous driving systems under rare but high-risk interactions. Existing diffusion-based methods offer str…
Coarse-to-Real: Generative Rendering for Populated Dynamic Scenes
Gonzalo Gomez-Nogales, Yicong Hong, Chongjian Ge +4
Traditional rendering pipelines rely on complex assets, accurate materials and lighting, and substantial computational resources to produce realistic imagery, yet they still face c…
Joint Diffusion for Universal Hand-Object Grasp Generation
Jinkun Cao, Jingyuan Liu, Kris Kitani +1
Predicting and generating human hand grasp over objects is critical for animation and robotic tasks. In this work, we focus on generating both the hand and objects in a grasp by a…
StrokeFusion: Vector Sketch Generation via Joint Stroke-UDF Encoding and Latent Sequence Diffusion
Jin Zhou, Yi Zhou, Hongliang Yang +2
In the field of sketch generation, raster-format trained models often produce non-stroke artifacts, while vector-format trained models typically lack a holistic understanding of sk…
HUMOTO: A 4D Dataset of Mocap Human Object Interactions
Jiaxin Lu, Chun-Hao Paul Huang, Uttaran Bhattacharya +2
We present Human Motions with Objects (HUMOTO), a high-fidelity dataset of human-object interactions for motion generation, computer vision, and robotics applications. Featuring 73…