activity
20242026
collaborators

10 papers

cs.CV2026

FilmBench: A Film-Grade Benchmark for Cinematic Video Generation

Shengyi Wang, Niantong Li, Guangzheng Hu +27

Progress in video generation keeps narrowing the visual gap between AI-generated and professionally produced footage, yet most benchmarks still draw prompts from web sources or LLM…

cs.CV2026

Lance: Unified Multimodal Modeling by Multi-Task Synergy

Fengyi Fu, Mengqi Huang, Shaojin Wu +10

We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather than relying on model capacity…

cs.CV2026

Seedance 2.0: Advancing Video Generation for World Complexity

Team Seedance, De Chen, Liyang Chen +168

Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…

cs.CL2026

Order Is Not Layout: Order-to-Space Bias in Image Generation

Yongkang Zhang, Zonglin Zhao, Yuechen Zhang +3

We study a systematic bias in modern image generation models: the mention order of entities in text spuriously determines spatial layout and entity--role binding. We term this phen…

cs.CV2025

DreamO: A Unified Framework for Image Customization

Chong Mou, Yanze Wu, Wenxu Wu +15

Recently, extensive research on image customization (e.g., identity, subject, style, background, etc.) demonstrates strong customization capabilities in large-scale generative mode…

cs.CV2025

RealCustom++: Representing Images as Real Textual Word for Real-Time Customization

Zhendong Mao, Mengqi Huang, Fei Ding +3

Given a text and an image of a specific subject, text-to-image customization aims to generate new images that align with both the text and the subject's appearance. Existing works…