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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.CV2026

MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation

Yujie Wei, Yujin Han, Zhekai Chen +20

Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However, evaluating such frontier mo…

cs.CV2026

Latent Spatial Memory for Video World Models

Weijie Wang, Haoyu Zhao, Yifan Yang +7

Video world models that maintain 3D spatial consistency across generated frames typically rely on explicit point cloud memory constructed in RGB space. This design is both computat…

cs.CV2026

ReCA: Multi-Shot Long Video Extrapolation via Recursive Context Allocation

Akide Liu, Jinbo Xing, Chaojie Mao +8

Minute-scale cinematic video generation is a central challenge for generative video models. Existing paradigms address only fragments of this challenge: single-shot extrapolation p…

cs.CV2026

World-R1: Reinforcing 3D Constraints for Text-to-Video Generation

Weijie Wang, Xiaoxuan He, Youping Gu +9

Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods attempt to inject 3D priors via…

cs.CV2026

FlashAR: Efficient Post-Training Acceleration for Autoregressive Image Generation

Junkang Zhou, Yefei He, Feng Chen +2

Large-scale autoregressive models have demonstrated remarkable capabilities in image generation. However, their sequential raster-scan decoding relies on strictly next-token predic…

cs.CV2026

Dynamic Execution Commitment of Vision-Language-Action Models

Feng Chen, Xianghui Wang, Yuxuan Chen +4

Vision-Language-Action (VLA) models predominantly adopt action chunking, i.e., predicting and committing to a short horizon of consecutive low-level actions in a single forward pas…

cs.CV2026

AesRM: Improving Video Aesthetics with Expert-Level Feedback

Yujin Han, Yujie Wei, Yefei He +7

Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyo…

cs.CV2026

Less Detail, Better Answers: Degradation-Driven Prompting for VQA

Haoxuan Han, Weijie Wang, Zeyu Zhang +2

Recent advancements in Vision-Language Models (VLMs) have significantly pushed the boundaries of Visual Question Answering (VQA).However,high-resolution details can sometimes becom…

cs.CV2026

LiveWorld: Simulating Out-of-Sight Dynamics in Generative Video World Models

Zicheng Duan, Jiatong Xia, Zeyu Zhang +7

Recent generative video world models aim to simulate visual environment evolution, allowing an observer to interactively explore the scene via camera control. However, they implici…

cs.CV2025

Wan-Move: Motion-controllable Video Generation via Latent Trajectory Guidance

Ruihang Chu, Yefei He, Zhekai Chen +10

We present Wan-Move, a simple and scalable framework that brings motion control to video generative models. Existing motion-controllable methods typically suffer from coarse contro…

cs.CV2025

ShowTable: Unlocking Creative Table Visualization with Collaborative Reflection and Refinement

Zhihang Liu, Xiaoyi Bao, Pandeng Li +7

While existing generation and unified models excel at general image generation, they struggle with tasks requiring deep reasoning, planning, and precise data-to-visual mapping abil…

cs.CV2024

OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation

Pengfei Zhou, Xiaopeng Peng, Jiajun Song +15

Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding and generation tasks. However, generating interleaved image-text content remains a ch…