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Zheng Zhu

8 papers indexed

arxivcs.CV2026-07-22

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching

Hao Wang, Haoran Geng, Xiaotong Yang, Jing Tang, Songlin Wei, Linlong Lang, et al.

Stereo matching is a fundamental task in 3D reconstruction. Despite remarkable advances, the prevailing paradigms formulate stereo matching as a deterministic regression problem, collapsing the multimodal distribution modeling into a single-point estimation. This formulation suff…

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arxivcs.RO2026-07-15

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

GigaWorld Team, Angen Ye, Angyuan Ma, Boyuan Wang, Chaojun Ni, Fangzheng Ye, et al.

World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as dense supervision for physically grounded action generation. However, a common design in existing WAMs is to explicitly generate fu…

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arxivcs.ROcs.HCeess.SY2026-07-15

Zero2Skill: Bootstrapping Robot Skills through Autonomous Data Collection, Training, and Deployment

Boyuan Wang, Zhenyuan Zhang, Zhiqin Yang, Peijun Gu, Shuya Wang, Xiaofeng Wang, et al.

Autonomous data collection governs the volume and quality of real-world trajectories for manipulation policy learning. Existing pipelines reduce human effort via self-resetting, VLM verification, or language-guided correction, yet episode-scoped fixes must be reissued whenever th…

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arxivcs.ROcs.AI2026-07-05

HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models

Angen Ye, Weijie Ke, Xiaofeng Wang, Xinze Chen, Chaojun Ni, Guosheng Zhao, et al.

World-action (WA) models can generate long-horizon action chunks for general-purpose robotic manipulation, but they remain vulnerable to calibration, perception, and contact-dynamics errors in real-world precision tasks, often failing in the final few millimeters of alignment or…

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arxivcs.RO2026-07-02

GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation

GigaWorld Team, Angyuan Ma, Boyuan Wang, Bohan Li, Chaojun Ni, Guo Li, et al.

Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, robotic policies require slow, costly real-world rollouts limited by hardware and human supervision, which has driven interest in w…

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arxivcs.CV2026-07-02

Bridging 3D Gaussians and Semantic Occupancy for Comprehensive Open-Vocabulary Scene Understanding from Unposed Images

Hu Zhu, Bohan Li, Xianda Guo, Yanlun Peng, Zheng Zhu, Xin Jin, et al.

Comprehensive 3D scene understanding from sparse, unposed images requires a model to recover renderable geometry, open-vocabulary semantics, and free/occupied 3D space without relying on external camera calibration. Recent feed-forward Gaussian methods improve pose-free reconstru…

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arxivcs.CV2026-07-01

AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting

Dexu Zhu, Jiangnan Shao, Xiaofeng Wang, Junxian Duan, Jie Cao, Zheng Zhu, et al.

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for high-fidelity rendering. However, existing assets often suffer from quality bottlenecks such as missing details and texture noise. Prior attempts to enhance these assets via 2D image processing introduce mu…

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arxivcs.RO2026-06-30

DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation

Ziyu Shan, Zhenyu Wu, Xiaofeng Wang, Zheng Zhu, Ziwei Wang

Video-based embodied world models provide an appealing substrate for robotic manipulation by predicting future states, yet current approaches remain limited by a fundamental entanglement: accurately modeling dynamics typically requires low-level temporal reasoning, while producin…

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