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cs.CV2026

ZipTok3D: High-Fidelity 3D Tokenization with Compact Token Prefixes

Mingda Lin, Weijie Wang, Zeyu Zhang +7

Compact token sequences are essential for efficient 3D generation. However, existing 3D tokenizers typically organize latent representations either over spatial regions or as fixed…

cs.CV2026

Block3D: Efficient Text-to-3D Generation via Block-Wise Diffusion

Bowen Cui, Weijie Wang, Zeyu Zhang +7

While text-to-3D generation has advanced rapidly, achieving high geometric fidelity at low inference cost remains challenging. Existing text-to-3D methods either decode discrete sh…

cs.CV2025

OmniSparse: Training-Aware Fine-Grained Sparse Attention for Long-Video MLLMs

Feng Chen, Yefei He, Shaoxuan He +9

Existing sparse attention methods primarily target inference-time acceleration by selecting critical tokens under predefined sparsity patterns. However, they often fail to bridge t…

cs.CV2025

BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation

Zeyu Zhang, Jinyuan Mao, Shuning Chang +5

Long video generation is a critical step toward building realistic world models, requiring both high visual fidelity and long-range interaction consistency. Recent autoregressive d…

cs.CV2025

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation

Inferix Team, Tianyu Feng, Yizeng Han +13

World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic, and interactive high-quality videos.…

cs.CV2025

FPSAttention: Training-Aware FP8 and Sparsity Co-Design for Fast Video Diffusion

Akide Liu, Zeyu Zhang, Zhexin Li +12

Diffusion generative models have become the standard for producing high-quality, coherent video content, yet their slow inference speeds and high computational demands hinder pract…