MIC-DKFZ/image-time-series
Code for deep learning-based glioma/tumor growth models (⭐ 27)
paraschopra/one-network-many-uses
Four-in-one deep network: image search, image captioning, similar words and similar images using a single model (⭐ 136)
NeuralFur: Animal Fur Reconstruction From Multi-View Images
Reconstructing realistic animal fur geometry from images is a challenging task due to the fine-scale details, self-occlusion, and view-dependent appearance of fur. In contrast to human hairstyle reconstruction, there are also no datasets that can be...
Bing Homepage Quiz (5/19/2024): Today's image takes us to one
Bing Homepage Quiz (5/19/2024): Today's image takes us to one of the five Italian villages known as the Cinque Terre. Which one is it?
Efficient Curation of Invertebrate Image Datasets Using Feature Embeddings and A…
The amount of image datasets collected for environmental monitoring purposes has increased in the past years as computer vision assisted methods have gained interest. Computer vision applications rely on high-quality datasets, making data curation im...
niyazed/Dermatology-Image-Classification
The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. (⭐ 16)
DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images
In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations, including a small number of image samples, limited disease conditions...
Enhanced Dermatology Image Quality Assessment via Cross-Domain Training
Teledermatology has become a widely accepted communication method in daily clinical practice, enabling remote care while showing strong agreement with in-person visits. Poor image quality remains an unsolved problem in teledermatology and is a major...
In Praise of Artifice Reloaded: Caution with subjective image quality databases
Subjective image quality databases are a major source of raw data on how the visual system works in naturalistic environments. These databases describe the sensitivity of many observers to a wide range of distortions (of different nature and with dif...
AI tool generates high-quality images faster than state-of-the-art ...
Mar 21, 2025 · A hybrid AI approach known as hybrid autoregressive transformer can generate realistic images with the same or better quality than state-of-the-art diffusion models, but that runs about nine …
Boosting in Image Quality Assessment
In this paper, we analyze the effect of boosting in image quality assessment through multi-method fusion. Existing multi-method studies focus on proposing a single quality estimator. On the contrary, we investigate the generalizability of multi-metho...
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Eno…
Previous work has shown the potential of deep learning to predict renal obstruction using kidney ultrasound images. However, these image-based classifiers have been trained with the goal of single-visit inference in mind. We compare methods from vide...
containers/skopeo
Work with remote images registries - retrieving information, images, signing content (⭐ 10538)
Understanding Retrieval Robustness for Retrieval-Augmented Image Captioning
Recent advances in retrieval-augmented models for image captioning highlight the benefit of retrieving related captions for efficient, lightweight models with strong domain-transfer capabilities. While these models demonstrate the success of retrieva...
NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
In this paper, we analyze and discuss ShadowFormer in preparation for the NTIRE2023 Shadow Removal Challenge [1], implementing five key improvements: image alignment, the introduction of a perceptual quality loss function, the semi-automatic annotati...
Masked-Attention Diffusion Guidance for Spatially Controlling Text-to-Image Gene…
Text-to-image synthesis has achieved high-quality results with recent advances in diffusion models. However, text input alone has high spatial ambiguity and limited user controllability. Most existing methods allow spatial control through additional...
Transform Network Architectures for Deep Learning based End-to-End Image/Video C…
Most of the existing deep learning based end-to-end image/video coding (DLEC) architectures are designed for non-subsampled RGB color format. However, in order to achieve a superior coding performance, many state-of-the-art block-based compression st...
Stress and Adaptation: Applying Anna Karenina Principle in Deep Learning for Ima…
Image classification with deep neural networks has reached state-of-art with high accuracy. This success is attributed to good internal representation features that bypasses the difficulties of the non-convex optimization problems. We have little und...
Lesion-Inspired Denoising Network: Connecting Medical Image Denoising and Lesion…
Deep learning has achieved notable performance in the denoising task of low-quality medical images and the detection task of lesions, respectively. However, existing low-quality medical image denoising approaches are disconnected from the detection t...
List of satellite map images with missing or unclear data - Wikipedia
This is a list of satellite map images with missing or unclear data. Some locations on free, publicly viewable satellite map services have such issues