arXiv:1712.03400
공식 코드 · Papers with Code
Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2
원문 초록
We review some of the most recent approaches to colorize gray-scale images using deep learning methods. Inspired by these, we propose a model which combines a deep Convolutional Neural Network trained from scratch with high-level features extracted from the Inception-ResNet-v2 pre-trained model. Thanks to its fully convolutional architecture, our encoder-decoder model can process images of any size and aspect ratio. Other than presenting the training results, we assess the "public acceptance" of the generated images by means of a user study. Finally, we present a carousel of applications on different types of images, such as historical photographs.
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Leveraging the Powerful Attention of a Pre-trained Diffusion Model for Exemplar-based Image Colorization
MTSIC: Multi-stage Transformer-based GAN for Spectral Infrared Image Colorization
Controllable Image Colorization with Instance-aware Texts and Masks
Invertible Grayscale via Dual Features Ensemble
Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
Sentinel: Decoding Context Utilization via Attention Probing for Efficient LLM Context Compression
토론
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