Papers Colorization
“Colorization” 태그가 달린 논문 367편 · 필터 해제
Visual Prompting via Image Inpainting
How does one adapt a pre-trained visual model to novel downstream tasks without task-specific finetuning or any model modification? Inspired by prompting in NLP, this paper investigates visual prompting: given input-outp…
ColorizationEdge DetectionForeground SegmentationImage Inpainting+4Cross-Camera Deep Colorization
In this paper, we consider the color-plus-mono dual-camera system and propose an end-to-end convolutional neural network to align and fuse images from it in an efficient and cost-effective way. Our method takes cross-dom…
ColorizationParaColorizer: Realistic Image Colorization using Parallel Generative Networks
Grayscale image colorization is a fascinating application of AI for information restoration. The inherently ill-posed nature of the problem makes it even more challenging since the outputs could be multi-modal. The learn…
ColorizationImage ColorizationMemory-Guided Collaborative Attention for Nighttime Thermal Infrared Image Colorization
Nighttime thermal infrared (NTIR) image colorization, also known as translation of NTIR images into daytime color images (NTIR2DC), is a promising research direction to facilitate nighttime scene perception for humans an…
ColorizationGenerative Adversarial NetworkImage ColorizationImage-to-Image Translation+3TIC: Text-Guided Image Colorization
Image colorization is a well-known problem in computer vision. However, due to the ill-posed nature of the task, image colorization is inherently challenging. Though several attempts have been made by researchers to make…
ColorizationImage ColorizationGLEAN: Generative Latent Bank for Image Super-Resolution and Beyond
We show that pre-trained Generative Adversarial Networks (GANs) such as StyleGAN and BigGAN can be used as a latent bank to improve the performance of image super-resolution. While most existing perceptual-oriented appro…
ColorizationDecoderImage ColorizationImage Restoration+2NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT Cameras
We present NeuriCam, a novel deep learning-based system to achieve video capture from low-power dual-mode IoT camera systems. Our idea is to design a dual-mode camera system where the first mode is low-power (1.1 mW) but…
ColorizationKey-Frame-based Video Super-Resolution (K = 15)Super-ResolutionVideo Super-ResolutionBigColor: Colorization using a Generative Color Prior for Natural Images
For realistic and vivid colorization, generative priors have recently been exploited. However, such generative priors often fail for in-the-wild complex images due to their limited representation space. In this paper, we…
ColorizationiColoriT: Towards Propagating Local Hint to the Right Region in Interactive Colorization by Leveraging Vision Transformer
Point-interactive image colorization aims to colorize grayscale images when a user provides the colors for specific locations. It is essential for point-interactive colorization methods to appropriately propagate user-pr…
ColorizationDecoderImage ColorizationPoint-interactive Image ColorizationEliminating Gradient Conflict in Reference-based Line-Art Colorization
Reference-based line-art colorization is a challenging task in computer vision. The color, texture, and shading are rendered based on an abstract sketch, which heavily relies on the precise long-range dependency modeling…
ColorizationLine Art ColorizationSSIMStyleFlow For Content-Fixed Image to Image Translation
Image-to-image (I2I) translation is a challenging topic in computer vision. We divide this problem into three tasks: strongly constrained translation, normally constrained translation, and weakly constrained translation.…
ColorizationImage-to-Image TranslationStyle TransferTranslationPolyU-BPCoMa: A Dataset and Benchmark Towards Mobile Colorized Mapping Using a Backpack Multisensorial System
Constructing colorized point clouds from mobile laser scanning and images is a fundamental work in surveying and mapping. It is also an essential prerequisite for building digital twins for smart cities. However, existin…
ColorizationImproving Diffusion Models for Inverse Problems using Manifold Constraints
Recently, diffusion models have been used to solve various inverse problems in an unsupervised manner with appropriate modifications to the sampling process. However, the current solvers, which recursively apply a revers…
ColorizationImage InpaintingImage Colorization using U-Net with Skip Connections and Fusion Layer on Landscape Images
We present a novel technique to automatically colorize grayscale images that combine the U-Net model and Fusion Layer features. This approach allows the model to learn the colorization of images from pre-trained U-Net. M…
ColorizationImage ColorizationUViM: A Unified Modeling Approach for Vision with Learned Guiding Codes
We introduce UViM, a unified approach capable of modeling a wide range of computer vision tasks. In contrast to previous models, UViM has the same functional form for all tasks; it requires no task-specific modifications…
ColorizationDepth EstimationDepth PredictionImage Colorization+3Pik-Fix: Restoring and Colorizing Old Photos
Restoring and inpainting the visual memories that are present, but often impaired, in old photos remains an intriguing but unsolved research topic. Decades-old photos often suffer from severe and commingled degradation s…
ColorizationTwo Decades of Colorization and Decolorization for Images and Videos
Colorization is a computer-aided process, which aims to give color to a gray image or video. It can be used to enhance black-and-white images, including black-and-white photos, old-fashioned films, and scientific imaging…
ColorizationImage EnhancementImage SegmentationSemantic Segmentation+1Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation
Recent works on 3D semantic segmentation propose to exploit the synergy between images and point clouds by processing each modality with a dedicated network and projecting learned 2D features onto 3D points. Merging larg…
3D Semantic SegmentationColorizationMultimodal Deep LearningSemantic SegmentationInfluence of Color Spaces for Deep Learning Image Colorization
Colorization is a process that converts a grayscale image into a color one that looks as natural as possible. Over the years this task has received a lot of attention. Existing colorization methods rely on different colo…
ColorizationDeep LearningImage ColorizationAnalysis of Different Losses for Deep Learning Image Colorization
Image colorization aims to add color information to a grayscale image in a realistic way. Recent methods mostly rely on deep learning strategies. While learning to automatically colorize an image, one can define well-sui…
ColorizationDeep LearningImage Colorization