4 citations · 10 across the 30 of their papers we have counts for
11 papers · 2 filters
MemFlow: Flowing Adaptive Memory for Consistent and Efficient Long Video Narratives
Sihui Ji, Xi Chen, Shuai Yang +3
The core challenge for streaming video generation is maintaining the content consistency in long context, which poses high requirement for the memory design. Most existing solution…
UnityVideo: Unified Multi-Modal Multi-Task Learning for Enhancing World-Aware Video Generation
Jiehui Huang, Yuechen Zhang, Xu He +7
Recent video generation models demonstrate impressive synthesis capabilities but remain limited by single-modality conditioning, constraining their holistic world understanding. Th…
Decoupling Complexity from Scale in Latent Diffusion Model
Tianxiong Zhong, Xingye Tian, Xuebo Wang +3
Existing latent diffusion models typically couple scale with content complexity, using more latent tokens to represent higher-resolution images or higher-frame rate videos. However…
Terra: Explorable Native 3D World Model with Point Latents
Yuanhui Huang, Weiliang Chen, Wenzhao Zheng +4
World models have garnered increasing attention for comprehensive modeling of the real world. However, most existing methods still rely on pixel-aligned representations as the basi…
PhysMaster: Mastering Physical Representation for Video Generation via Reinforcement Learning
Sihui Ji, Xi Chen, Xin Tao +2
Video generation models nowadays are capable of generating visually realistic videos, but often fail to adhere to physical laws, limiting their ability to generate physically plaus…
Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?
Ouxiang Li, Yuan Wang, Xinting Hu +7
Text-to-image (T2I) generation aims to synthesize images from textual prompts, which jointly specify what must be shown and imply what can be inferred, which thus correspond to two…
MIDAS: Multimodal Interactive Digital-humAn Synthesis via Real-time Autoregressive Video Generation
Ming Chen, Liyuan Cui, Wenyuan Zhang +9
Recently, interactive digital human video generation has attracted widespread attention and achieved remarkable progress. However, building such a practical system that can interac…
DiffCap: Diffusion-based Real-time Human Motion Capture using Sparse IMUs and a Monocular Camera
Shaohua Pan, Xinyu Yi, Yan Zhou +4
Combining sparse IMUs and a monocular camera is a new promising setting to perform real-time human motion capture. This paper proposes a diffusion-based solution to learn human mot…
Training-Free Efficient Video Generation via Dynamic Token Carving
Yuechen Zhang, Jinbo Xing, Bin Xia +6
Despite the remarkable generation quality of video Diffusion Transformer (DiT) models, their practical deployment is severely hindered by extensive computational requirements. This…
VFRTok: Variable Frame Rates Video Tokenizer with Duration-Proportional Information Assumption
Tianxiong Zhong, Xingye Tian, Boyuan Jiang +4
Modern video generation frameworks based on Latent Diffusion Models suffer from inefficiencies in tokenization due to the Frame-Proportional Information Assumption. Existing tokeni…
BadVideo: Stealthy Backdoor Attack against Text-to-Video Generation
Ruotong Wang, Mingli Zhu, Jiarong Ou +4
Text-to-video (T2V) generative models have rapidly advanced and found widespread applications across fields like entertainment, education, and marketing. However, the adversarial v…