StreamingEffect enables real-time 720p human-centric video effect generation on one GPU via teacher-student distillation, keyframe control, and a new 130K video dataset.
Relationadapter: Learning and transferring visual relation with diffusion transformers
5 Pith papers cite this work. Polarity classification is still indexing.
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MirrorPPR extracts retouching operations from exemplar pairs via a dedicated extractor and transfers them to query images through a LoRA-adapted Diffusion Transformer, enabled by a new 47-million-pair dataset and self-augmentation for alignment.
A 4D try-on proxy (3DGS avatar + SMPL-X + background points) anchors a DiT so virtual try-on videos can follow arbitrary camera trajectories with consistent garments and scene structure.
VISTA introduces a new synthetic triplet dataset and diffusion-transformer framework with style adapter that jointly models style, content, and motion to achieve state-of-the-art video style transfer.
SWEET is a one-shot sparse visual planning framework that progressively generates manipulation keyframes via image editing conditioned on language and spatial guidance, then converts them to actions with a diffusion predictor, showing better fidelity and lower cost than video models on DROID and Rob
citing papers explorer
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StreamingEffect: Real-Time Human-Centric Video Effect Generation
StreamingEffect enables real-time 720p human-centric video effect generation on one GPU via teacher-student distillation, keyframe control, and a new 130K video dataset.
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MirrorPPR: Exemplar-Based Portrait Photo Retouching
MirrorPPR extracts retouching operations from exemplar pairs via a dedicated extractor and transfers them to query images through a LoRA-adapted Diffusion Transformer, enabled by a new 47-million-pair dataset and self-augmentation for alignment.
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TryOnCrafter: Unleashing Camera Trajectories for Realistic Video Virtual Try-on via a Renderable 4D Try-on Proxy
A 4D try-on proxy (3DGS avatar + SMPL-X + background points) anchors a DiT so virtual try-on videos can follow arbitrary camera trajectories with consistent garments and scene structure.
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VISTA: Triplet-Supervised Video Style Transfer with Diffusion Transformers
VISTA introduces a new synthetic triplet dataset and diffusion-transformer framework with style adapter that jointly models style, content, and motion to achieve state-of-the-art video style transfer.
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SWEET: Sparse World Modeling with Image Editing for Embodied Task Execution
SWEET is a one-shot sparse visual planning framework that progressively generates manipulation keyframes via image editing conditioned on language and spatial guidance, then converts them to actions with a diffusion predictor, showing better fidelity and lower cost than video models on DROID and Rob