2 citations · 5 across the 21 of their papers we have counts for
14 papers · 1 filter
BAgger: Backwards Aggregation for Mitigating Drift in Autoregressive Video Diffusion Models
Ryan Po, Eric Ryan Chan, Changan Chen +1
Autoregressive video models are promising for world modeling via next-frame prediction, but they suffer from exposure bias: a mismatch between training on clean contexts and infere…
BulletTime: Decoupled Control of Time and Camera Pose for Video Generation
Yiming Wang, Qihang Zhang, Shengqu Cai +7
Emerging video diffusion models achieve high visual fidelity but fundamentally couple scene dynamics with camera motion, limiting their ability to provide precise spatial and tempo…
Taming Flow-based I2V Models for Creative Video Editing
Xianghao Kong, Hansheng Chen, Yuwei Guo +4
Although image editing techniques have advanced significantly, video editing, which aims to manipulate videos according to user intent, remains an emerging challenge. Most existing…
Mixture of Contexts for Long Video Generation
Shengqu Cai, Ceyuan Yang, Lvmin Zhang +10
Long video generation is fundamentally a long context memory problem: models must retain and retrieve salient events across a long range without collapsing or drifting. However, sc…
Towards Vision-Language-Garment Models for Web Knowledge Garment Understanding and Generation
Jan Ackermann, Kiyohiro Nakayama, Guandao Yang +2
Multimodal foundation models have demonstrated strong generalization, yet their ability to transfer knowledge to specialized domains such as garment generation remains underexplore…
Video World Models with Long-term Spatial Memory
Tong Wu, Shuai Yang, Ryan Po +4
Emerging world models autoregressively generate video frames in response to actions, such as camera movements and text prompts, among other control signals. Due to limited temporal…
Long-Context State-Space Video World Models
Ryan Po, Yotam Nitzan, Richard Zhang +5
Video diffusion models have recently shown promise for world modeling through autoregressive frame prediction conditioned on actions. However, they struggle to maintain long-term m…
Interspatial Attention for Efficient 4D Human Video Generation
Ruizhi Shao, Yinghao Xu, Yujun Shen +5
Generating photorealistic videos of digital humans in a controllable manner is crucial for a plethora of applications. Existing approaches either build on methods that employ templ…
GenDoP: Auto-regressive Camera Trajectory Generation as a Director of Photography
Mengchen Zhang, Tong Wu, Jing Tan +3
Camera trajectory design plays a crucial role in video production, serving as a fundamental tool for conveying directorial intent and enhancing visual storytelling. In cinematograp…
GroomLight: Hybrid Inverse Rendering for Relightable Human Hair Appearance Modeling
Yang Zheng, Menglei Chai, Delio Vicini +5
We present GroomLight, a novel method for relightable hair appearance modeling from multi-view images. Existing hair capture methods struggle to balance photorealistic rendering wi…
CameraCtrl II: Dynamic Scene Exploration via Camera-controlled Video Diffusion Models
Hao He, Ceyuan Yang, Shanchuan Lin +7
This paper introduces CameraCtrl II, a framework that enables large-scale dynamic scene exploration through a camera-controlled video diffusion model. Previous camera-conditioned v…
3DGen-Bench: Comprehensive Benchmark Suite for 3D Generative Models
Yuhan Zhang, Mengchen Zhang, Tong Wu +4
3D generation is experiencing rapid advancements, while the development of 3D evaluation has not kept pace. How to keep automatic evaluation equitably aligned with human perception…
FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Views
Shangzhan Zhang, Jianyuan Wang, Yinghao Xu +5
We present FLARE, a feed-forward model designed to infer high-quality camera poses and 3D geometry from uncalibrated sparse-view images (i.e., as few as 2-8 inputs), which is a cha…
RelightVid: Temporal-Consistent Diffusion Model for Video Relighting
Ye Fang, Zeyi Sun, Shangzhan Zhang +6
Diffusion models have demonstrated remarkable success in image generation and editing, with recent advancements enabling albedo-preserving image relighting. However, applying these…