Image Animation
15 papers with code • 0 benchmarks • 0 datasets
Image Animation is a field for image-animation of a source image by a driving video
Benchmarks
These leaderboards are used to track progress in Image Animation
Most implemented papers
First Order Motion Model for Image Animation
AliaksandrSiarohin/first-order-model
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NeurIPS 2019
To achieve this, we decouple appearance and motion information using a self-supervised formulation.
Image Animation with Perturbed Masks
itsyoavshalev/Image-Animation-with-Perturbed-Masks
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CVPR 2022
We present a novel approach for image-animation of a source image by a driving video, both depicting the same type of object.
Animating Arbitrary Objects via Deep Motion Transfer
AliaksandrSiarohin/monkey-net
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CVPR 2019
This is achieved through a deep architecture that decouples appearance and motion information.
Creative Flow+ Dataset
We present the Creative Flow+ Dataset, the first diverse multi-style artistic video dataset richly labeled with per-pixel optical flow, occlusions, correspondences, segmentation labels, normals, and depth.
Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation
RenYurui/Global-Flow-Local-Attention
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We show that our framework can spatially transform the inputs in an efficient manner.
Ultra-low bitrate video conferencing using deep image animation
In this work we propose a novel deep learning approach for ultra-low bitrate video compression for video conferencing applications.
PriorityCut: Occlusion-guided Regularization for Warp-based Image Animation
State-of-the-art self-supervised image animation approaches warp the source image according to the motion of the driving video and recover the warping artifacts by inpainting.
DeepFake MNIST+: A DeepFake Facial Animation Dataset
It includes 10, 000 facial animation videos in ten different actions, which can spoof the recent liveness detectors.
Latent Image Animator: Learning to animate image via latent space navigation
Deviating from such models, we here introduce Latent Image Animator (LIA), a self-supervised auto-encoder that evades need for structure representation.
Neural Fields in Visual Computing and Beyond
nvidiagameworks/kaolin-wisp
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Recent advances in machine learning have created increasing interest in solving visual computing problems using a class of coordinate-based neural networks that parametrize physical properties of scenes or objects across space and time.
