7 accepted papers
Recent progress in video diffusion models has enabled remarkable generative fidelity, yet leveraging these priors for restoration remains limited by the strong coupling between conditional and unconditional branches in standard classifier-free guidance. We introduce a training-free framework that en
Current autoregressive video diffusion models are constrained by three core bottlenecks: (i) the finite temporal horizon imposed by the base model's 3D Rotary Positional Embedding (3D-RoPE), (ii) slow prompt responsiveness in maintaining fine-grained action control during long-form rollouts, and (ii
Text-to-video models have demonstrated impressive capabilities in producing diverse video content, yet often lack fine-grained control over motion. We address the problem of motion transfer: given a source video and a target text prompt, generate a new video that preserves the source motion while ma
In this work, we address dynamic view synthesis from monocular videos as an inverse problem in a training-free setting. By redesigning the noise initialization phase of a pre-trained video diffusion model, we enable high-fidelity dynamic view synthesis without any weight updates or auxiliary modules…
We introduce LoRAShop, the first framework for multi-concept image generation and editing with LoRA models. LoRAShop builds on a key observation about the feature interaction patterns inside Flux-style diffusion transformers: concept-specific transformer features activate spatially coherent regions…
Recent advancements in diffusion-based models have demonstrated significant success in generating images from text. However video editing models have not yet reached the same level of visual quality and user control. To address this we introduce RAVE a zero-shot video editing method that leverages p…
Text-to-image models are becoming increasingly popular, revolutionizing the landscape of digital art creation by enabling highly detailed and creative visual content generation. These models have been widely employed across various domains, particularly in art generation, where they facilitate a bro…