Papers Appearance Transfer
“Appearance Transfer” 태그가 달린 논문 32편 · 필터 해제
Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling
We present a new method for few-shot human motion transfer that achieves realistic human image generation with only a small number of appearance inputs. Despite recent advances in single person motion transfer, prior met…
Appearance TransferImage GenerationStyle and Pose Control for Image Synthesis of Humans from a Single Monocular View
Photo-realistic re-rendering of a human from a single image with explicit control over body pose, shape and appearance enables a wide range of applications, such as human appearance transfer, virtual try-on, motion imita…
Appearance TransferImage GenerationNovel View SynthesisVirtual Try-onLiquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis
We tackle human image synthesis, including human motion imitation, appearance transfer, and novel view synthesis, within a unified framework. It means that the model, once being trained, can be used to handle all these t…
Appearance TransferDenoisingImage GenerationNovel View SynthesisTwo-Stream Appearance Transfer Network for Person Image Generation
Pose guided person image generation means to generate a photo-realistic person image conditioned on an input person image and a desired pose. This task requires spatial manipulation of the source image according to the t…
Appearance TransferImage GenerationTranslationVocal Bursts Valence PredictionNeural Crossbreed: Neural Based Image Metamorphosis
We propose Neural Crossbreed, a feed-forward neural network that can learn a semantic change of input images in a latent space to create the morphing effect. Because the network learns a semantic change, a sequence of me…
Appearance TransferImage MorphingStyle TransferVideo Frame InterpolationPose-Guided High-Resolution Appearance Transfer via Progressive Training
We propose a novel pose-guided appearance transfer network for transferring a given reference appearance to a target pose in unprecedented image resolution (1024 * 1024), given respectively an image of the reference and …
Appearance TransferDecoderVideo GenerationVocal Bursts Intensity PredictionLiquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
We tackle the human motion imitation, appearance transfer, and novel view synthesis within a unified framework, which means that the model once being trained can be used to handle all these tasks. The existing task-speci…
Appearance TransferDenoisingNovel View SynthesisUnsupervised Part-Based Disentangling of Object Shape and Appearance
Large intra-class variation is the result of changes in multiple object characteristics. Images, however, only show the superposition of different variable factors such as appearance or shape. Therefore, learning to dise…
Appearance TransferImage GenerationObjectPose Prediction+3Human Appearance Transfer
We propose an automatic person-to-person appearance transfer model based on explicit parametric 3d human representations and learned, constrained deep translation network architectures for photographic image synthesis. G…
Appearance TransferImage GenerationAdversarial Training for Adverse Conditions: Robust Metric Localisation using Appearance Transfer
We present a method of improving visual place recognition and metric localisation under very strong appear- ance change. We learn an invertable generator that can trans- form the conditions of images, e.g. from day to ni…
Appearance TransferVisual Place RecognitionModeling Object Appearance Using Context-Conditioned Component Analysis
Subspace models have been very successful at modeling the appearance of structured image datasets when the visual objects have been aligned in the images (e.g., faces). Even with extensions that allow for global transfor…
Appearance TransferObjectWeakly Supervised Localization of Novel Objects Using Appearance Transfer
We consider the problem of localizing unseen objects in weakly labeled image collections. Given a set of images annotated at the image level, our goal is to localize the object in each image. The novelty of our proposed …
Appearance TransferObject