Achieving stable and diverse dexterous grasping of deformable objects remains a fundamental challenge in robotics, due to high-dimensional action spaces and complex material properties. In this paper, we propose DeformableGrasp, a multimodal perception-guided reinforcement learning framework that enables adaptive grasp...
Ke-Yu Wang, Bing-Cong Lu, Zheng-Xue Cheng et al.· Proceedings of the 2nd Inter...· 0 citations
Speech compression is increasingly important in scenarios such as real-time and satellite communication. Neural codecs have shown superior Rate-Distortion (RD) performance over traditional signal-processing codecs. Models with long-range dependency encoders/decoders and entropy models outperform convolution-based struc...
Yu-Han Liu, Jun Xu, Feng-Xi Zhang et al.· 0 citations
Reconstructing 3D scenes from sparse views without per-scene optimization remains highly challenging, especially for recovering accurate geometry and fine textures. While recent feedforward approaches leverage generalizable 3D Gaussian Splatting (3DGS) for scene generation, they typically assign one or multiple Gaussia...
Bing He, Jing-Nan Gao, Yu-Nuo Chen et al.· 0 citations
Vision-language models are extending video understanding from offline clip analysis to continuous interactive streaming, but most research still emphasizes model capability rather than deployable low-latency interaction. This paper presents a unified edge-cloud system for real-time video VLM applications. Lightweight p...
Pu-Nan Dai, Jun Xu, Bing-Cong Lu et al.· 0 citations
Distributed deployment of large vision foundation models often partitions a ViT backbone and exchanges intermediate token features between computing nodes, making efficient feature compression critical under bandwidth and computation constraints. Existing ViT feature codecs typically flatten heterogeneous global and pa...
Donghui Feng, Feng-Xi Zhang, Changsheng Gao et al.· 0 citations
AdvDex is presented, a unified Vision-Language-Action framework for learning dexterous manipulation from human and robot demonstrations and the Joint-Aligned Action Space (JAAS) is proposed, a canonical action representation comprising an $\mathrm{SE}(3)$ wrist pose and 15 finger joints, thereby functionally aligning h...
Zhi-Yue Zhao, Jing Wu, Hairuo Liu et al.· 1 citation
Overall, EgoTac provides a scalable pathway to extract tactile priors from egocentric human videos, enabling broadly applicable tactile-aware robot learning.
The decoupled self-forcing distillation resolves both models under one frozen teacher: conditioned on motion, it distills the renderer into a block-causal student; unconditionally, it scores rendered rollouts against real videos, supervising motion by the video it produces.
Yan-Ru An, Rui-Yan Wang, Wen-Wu Wei et al.· 0 citations
MIE-Bench is introduced, the first large-scale multiple image editing benchmark with fine-grained human preference annotations and MIEScore, a multimodal large language model (MLLM)-based evaluation model enhanced with skill optimization and multi-dimensional supervised fine-tuning, to provide human-aligned feedback fo...
Zi-Tong Xu, Huiyu Duan, Xinyu Zhang et al.· 0 citations
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