1 citations · 1 across the 8 of their papers we have counts for
6 papers · 1 filter
KwaiMind Technical Report
Junlong Wu, Zijun Li, Yuting Hu +14
Commercial image editing requires product identity preservation, accurate text rendering, and user appeal alongside general editing quality. We present KwaiMind, an image editing s…
Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching
Jiuzhou Lin, Junlong Wu, Fei Zuo +11
Aligning video generative models to human preferences heavily relies on Reinforcement Learning (RL), which suffers from extensive computational overhead. Existing workflows typical…
CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
Jiyuan Wang, Huan Ouyang, Jiuzhou Lin +15
In this paper, we propose Concentrate and Concentrate (CaC), a coarse-to-fine anomaly reward model based on Vision-Language Models. During inference, it first conducts a global tem…
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…
Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Team Seedance, Heyi Chen, Siyan Chen +194
Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Yu Gao, Haoyuan Guo, Tuyen Hoang +41
Notable breakthroughs in diffusion modeling have propelled rapid improvements in video generation, yet current foundational model still face critical challenges in simultaneously b…