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Found 5 papers, 2 papers with code
AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning
We validate the proposed strategy in image-conditioned video generation and layout-conditioned video generation, all achieving top-performing results.
Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling
For the first stage, we propose a diffusion-based motion field predictor, which focuses on deducing the trajectories of the reference image's pixels.
Context-PIPs: Persistent Independent Particles Demands Spatial Context Features
We tackle the problem of Persistent Independent Particles (PIPs), also called Tracking Any Point (TAP), in videos, which specifically aims at estimating persistent long-term trajectories of query points in videos.
VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation
We first propose a TRi-frame Optical Flow (TROF) module that estimates bi-directional optical flows for the center frame in a three-frame manner.
NeuralMarker: A Framework for Learning General Marker Correspondence
We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker.
