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cs.CV2025

X-Humanoid: Robotize Human Videos to Generate Humanoid Videos at Scale

Pei Yang, Hai Ci, Yiren Song +1

The advancement of embodied AI has unlocked significant potential for intelligent humanoid robots. However, progress in both Vision-Language-Action (VLA) models and world models is…

cs.CV2025

B2N3D: Progressive Learning from Binary to N-ary Relationships for 3D Object Grounding

Feng Xiao, Hongbin Xu, Hai Ci +1

Localizing 3D objects using natural language is essential for robotic scene understanding. The descriptions often involve multiple spatial relationships to distinguish similar obje…

cs.CV2025

DiffSeg30k: A Multi-Turn Diffusion Editing Benchmark for Localized AIGC Detection

Hai Ci, Ziheng Peng, Pei Yang +2

Diffusion-based editing enables realistic modification of local image regions, making AI-generated content harder to detect. Existing AIGC detection benchmarks focus on classifying…

cs.CV2025

Cyc3D: Fine-grained Controllable 3D Generation via Cycle Consistency Regularization

Hongbin Xu, Chaohui Yu, Feng Xiao +5

Despite the remarkable progress of 3D generation, achieving controllability, i.e., ensuring consistency between generated 3D content and input conditions like edge and depth, remai…

cs.CV2025

Impossible Videos

Zechen Bai, Hai Ci, Mike Zheng Shou

Synthetic videos nowadays is widely used to complement data scarcity and diversity of real-world videos. Current synthetic datasets primarily replicate real-world scenarios, leavin…

cs.CV2024

Anti-Reference: Universal and Immediate Defense Against Reference-Based Generation

Yiren Song, Shengtao Lou, Xiaokang Liu +4

Diffusion models have revolutionized generative modeling with their exceptional ability to produce high-fidelity images. However, misuse of such potent tools can lead to the creati…