Papers Colorization
“Colorization” 태그가 달린 논문 367편 · 필터 해제
Transfer of Representations to Video Label Propagation: Implementation Factors Matter
This work studies feature representations for dense label propagation in video, with a focus on recently proposed methods that learn video correspondence using self-supervised signals such as colorization or temporal cyc…
ColorizationVirtual Histological Staining of Label-Free Total Absorption Photoacoustic Remote Sensing (TA-PARS)
Histopathological visualizations are a pillar of modern medicine and biological research. Surgical oncology relies exclusively on post-operative histology to determine definitive surgical success and guide adjuvant treat…
ColorizationDiagnosticGenerative Adversarial NetworkBias in Automated Image Colorization: Metrics and Error Types
We measure the color shifts present in colorized images from the ADE20K dataset, when colorized by the automatic GAN-based DeOldify model. We introduce fine-grained local and regional bias measurements between the origin…
ColorizationImage ColorizationA Deep Learning Approach for Digital Color Reconstruction of Lenticular Films
We propose the first accurate digitization and color reconstruction process for historical lenticular film that is robust to artifacts. Lenticular films emerged in the 1920s and were one of the first technologies that pe…
ColorizationData AugmentationPatch-Based Stochastic Attention for Image Editing
Attention mechanisms have become of crucial importance in deep learning in recent years. These non-local operations, which are similar to traditional patch-based methods in image processing, complement local convolutions…
ColorizationImage ColorizationImage InpaintingImage Super-Resolution+1ROMNet: Renovate the Old Memories
Renovating the memories in old photos is an intriguing research topic in computer vision fields. These legacy images often suffer from severe and commingled degradations such as cracks, noise, and color-fading, while lac…
ColorizationDenoising Diffusion Restoration Models
Many interesting tasks in image restoration can be cast as linear inverse problems. A recent family of approaches for solving these problems uses stochastic algorithms that sample from the posterior distribution of natur…
ColorizationDeblurringDenoisingImage Restoration+2Hiding Data in Colors: Secure and Lossless Deep Image Steganography via Conditional Invertible Neural Networks
Deep image steganography is a data hiding technology that conceal data in digital images via deep neural networks. However, existing deep image steganography methods only consider the visual similarity of container image…
ColorizationImage ColorizationImage SteganographySteganalysisSCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution
In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-sampling operation for the target device. Ho…
ColorizationImage ColorizationSuper-ResolutionStyle-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization
In this study, we present a colorization network that generates flat-color icons according to given sketches and semantic colorization styles. Specifically, our network contains a style-structure disentangled coloriz…
ColorizationDecoderDiversityImage-to-Image TranslationAstronomical Image Colorization and upscaling with Generative Adversarial Networks
Automatic colorization of images without human intervention has been a subject of interest in the machine learning community for a brief period of time. Assigning color to an image is a highly ill-posed problem because o…
ColorizationImage ColorizationImage Super-ResolutionSuper-ResolutionSemantic-Sparse Colorization Network for Deep Exemplar-based Colorization
Exemplar-based colorization approaches rely on reference image to provide plausible colors for target gray-scale image. The key and difficulty of exemplar-based colorization is to establish an accurate correspondence bet…
ColorizationEfficient Anomaly Detection Using Self-Supervised Multi-Cue Tasks
Anomaly detection is important in many real-life applications. Recently, self-supervised learning has greatly helped deep anomaly detection by recognizing several geometric transformations. However these methods lack fin…
Anomaly DetectionColorizationFace Anti-SpoofingObject+4AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactment
We present a novel Animation CelebHeads dataset (AnimeCeleb) to address an animation head reenactment. Different from previous animation head datasets, we utilize 3D animation models as the controllable image samplers, w…
ColorizationFace ReenactmentTalking Head GenerationPalette: Image-to-Image Diffusion Models
This paper develops a unified framework for image-to-image translation based on conditional diffusion models and evaluates this framework on four challenging image-to-image translation tasks, namely colorization, inpaint…
ColorizationDenoisingDiversityImage-to-Image Translation+4A Deep Learning Generative Model Approach for Image Synthesis of Plant Leaves
Objectives. We generate via advanced Deep Learning (DL) techniques artificial leaf images in an automatized way. We aim to dispose of a source of training samples for AI applications for modern crop management. Such appl…
Anomaly DetectionColorizationImage GenerationManagement+1Self-Supervised Learning Disentangled Group Representation as Feature
A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics). In this paper, we formulate the notion of …
ColorizationContrastive LearningSelf-Supervised LearningGenerative Flows as a General Purpose Solution for Inverse Problems
Due to the success of generative flows to model data distributions, they have been explored in inverse problems. Given a pre-trained generative flow, previous work proposed to minimize the 2-norm of the latent variables …
ColorizationDeblurringDenoisingImage Deblurring+3Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples
Convolutional Neural Networks (CNNs) for visual tasks are believed to learn both the low-level textures and high-level object attributes, throughout the network depth. This paper further investigates the `texture bias' i…
Colorizationimage-classificationImage Classificationobject-detection+1Temporally Consistent Video Colorization with Deep Feature Propagation and Self-regularization Learning
Video colorization is a challenging and highly ill-posed problem. Although recent years have witnessed remarkable progress in single image colorization, there is relatively less research effort on video colorization and …
ColorizationImage Colorization