1 citations · 4 across the 49 of their papers we have counts for
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PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control
Chuhao Chen, Peter Wonka, Chaoyang Wang +4
Interactive control for video generation is moving from coarse prompts toward fine-grained, physically meaningful manipulation of dynamic scenes. Yet existing controllable methods…
EgoPlay: Event-Triggered Video Editing for Egocentric Streams
Jinjie Mai, Gordon Guocheng Qian, Willi Menapace +8
We introduce EgoPlay, an event-triggered video-to-video editor for egocentric streams, obtained by fine-tuning a pretrained V2V diffusion transformer on event-conditioned data buil…
RegHead: Non-Humanoid Head Blendshapes via Feed-Forward Registration
Jiahao Luo, Hao Zhang, Jianqi Chen +9
We present RegHead, a framework for constructing semantic blendshape sets for animatable non-humanoid head avatars. With a fixed expression vocabulary, semantic blendshapes provide…
CineOrchestra: Unified Entity-Centric Conditioning for Cinematic Video Generation
Sharath Girish, Tsai-Shien Chen, Zhikang Dong +4
Cinematic video depicts multiple subjects acting or interacting at specific moments, captured with deliberate camera movement, and stitched together by shot transitions. Together,…
MeshLoom: Feed-Forward Non-Rigid Registration of Mesh Sequences
Jianqi Chen, Jiraphon Yenphraphai, Xiangjun Tang +4
We present MeshLoom, a feed-forward registration network that directly reconstructs vertex deformations across mesh sequences. Our approach advances non-rigid registration beyond e…
GeoStream: Toward Precise Camera Controlled Streaming Video Generation
Yizhou Zhao, Yifan Wang, Xiaoyuan Wang +11
Accurate interactive camera control is essential for video-based world models, but most existing approaches learn camera motion implicitly, leading to inaccurate control under out-…
Prompt2Effect: Training-Free Image-to-Video Model Specialization via LoRA Generation
Xiaomeng Yang, Yanyu Li, Gordon Guocheng Qian +7
While personalizing Image-to-Video (I2V) diffusion models with specific visual effects is increasingly demanded for high-end generation, current practice requires training a separa…
Helix4D: Complex 4D Mesh Generation
Jiraphon Yenphraphai, Jianqi Chen, Jian Wang +6
Current video-to-4D methods struggle with complex topology changes, transparent materials, thin structures, and inner surfaces. We present Helix4D, a dynamic mesh generation framew…
ActionParty: Multi-Subject Action Binding in Generative Video Games
Alexander Pondaven, Ziyi Wu, Igor Gilitschenski +4
Recent advances in video diffusion have enabled the development of "world models" capable of simulating interactive environments. However, these models are largely restricted to si…
EFlow: Fast Few-Step Video Generator Training from Scratch via Efficient Solution Flow
Dogyun Park, Yanyu Li, Sergey Tulyakov +1
Scaling video diffusion transformers is fundamentally bottlenecked by two compounding costs: the expensive quadratic complexity of attention per step, and the iterative sampling st…
One Model, Many Budgets: Elastic Latent Interfaces for Diffusion Transformers
Moayed Haji-Ali, Willi Menapace, Ivan Skorokhodov +6
Diffusion transformers (DiTs) achieve high generative quality but lock FLOPs to image resolution, limiting principled latency-quality trade-offs, and allocate computation uniformly…
Tuning-free Visual Effect Transfer across Videos
Maxwell Jones, Rameen Abdal, Or Patashnik +4
We present RefVFX, a new framework that transfers complex temporal effects from a reference video onto a target video or image in a feed-forward manner. While existing methods exce…
ArtifactLens: Hundreds of Labels Are Enough for Artifact Detection with VLMs
James Burgess, Rameen Abdal, Dan Stoddart +3
Modern image generators produce strikingly realistic images, where only artifacts like distorted hands or warped objects reveal their synthetic origin. Detecting these artifacts is…
Visual Personalization Turing Test
Rameen Abdal, James Burgess, Sergey Tulyakov +1
We introduce the Visual Personalization Turing Test (VPTT), a new paradigm for evaluating contextual visual personalization based on perceptual indistinguishability, rather than id…
OmniView: An All-Seeing Diffusion Model for 3D and 4D View Synthesis
Xiang Fan, Sharath Girish, Vivek Ramanujan +6
Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, i…
S2DiT: Sandwich Diffusion Transformer for Mobile Streaming Video Generation
Lin Zhao, Yushu Wu, Aleksei Lebedev +11
Diffusion Transformers (DiTs) have recently improved video generation quality. However, their heavy computational cost makes real-time or on-device generation infeasible. In this w…
SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices
Dongting Hu, Aarush Gupta, Magzhan Gabidolla +12
Recent advances in diffusion transformers (DiTs) have set new standards in image generation, yet remain impractical for on-device deployment due to their high computational and mem…
Diffusion-DRF: Free, Rich, and Differentiable Reward for Video Diffusion Fine-Tuning
Yifan Wang, Yanyu Li, Gordon Guocheng Qian +3
Video diffusion alignment has been heavily relied on scalar rewards. These rewards are typically derived from learned reward models in human preference datasets, requiring addition…