7 papers · 1 filter
ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training
Xionghao Wu, Yijun Yang, Shiyang Zhou +17
Robotic manipulation faces a fundamental scaling challenge: robust generalization demands broad physical experience, yet action-labeled robot trajectories are expensive to collect…
JoyAI-Video-Edit: Real-Time Open-Ended Video Editing with Autoregressive Diffusion
Yicheng Xiao, Wenxun Dai, Xinran Qin +22
Real-time video editing requires low-latency causal generation with bounded computational resources while preserving source fidelity and long-term temporal consistency. We present…
Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On
Yong Liu, Xiaolong Fu, Zihang Xu +10
We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is fashion-native, built for t…
Perceptual Flow Matching for Few-Step Generative Modeling
Chuyang Zhao, Yifei Song, Hongfa Wang +7
We propose Perceptual Flow Matching (PFM), a simple yet effective framework for few-step generation in flow-matching models. Rather than performing velocity regression in the conve…
Teacher-Feature Drifting: One-Step Diffusion Distillation with Pretrained Diffusion Representations
Yuan Zhang, Chenyi Li, Haodong Yu +8
Sampling from pretrained diffusion and flow-matching models typically requires many forward passes to generate diverse and high-fidelity images. Existing distillation methods often…
STORYANCHORS: Generating Consistent Multi-Scene Story Frames for Long-Form Narratives
Bo Wang, Haoyang Huang, Zhiying Lu +6
This paper introduces StoryAnchors, a unified framework for generating high-quality, multi-scene story frames with strong temporal consistency. The framework employs a bidirectiona…
Generative Pre-trained Autoregressive Diffusion Transformer
Yuan Zhang, Jiacheng Jiang, Guoqing Ma +5
In this work, we present GPDiT, a Generative Pre-trained Autoregressive Diffusion Transformer that unifies the strengths of diffusion and autoregressive modeling for long-range vid…