pavelgonchar
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Fast Differentiable Sorting and Ranking
Efficient vision foundation models for high-resolution generation and perception.
Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
EVA Series: Visual Representation Fantasies from BAAI
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
The TrueSkill Through Time Python Package
A library to apply some data augmentations in semantic segmentation problems
Hunt down social media accounts by username across social networks
The official project website of "Augmentation-free Dense Contrastive Distillation for Efficient Semantic Segmentation" (Af-DCD for short, accepted to NeurIPS 2023).
A general representation model across vision, audio, language modalities. Paper: ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
FyuseNet is an OpenGL(ES) based library that allows to run neural network inference on GPUs that support OpenGL or OpenGL/ES, which is the case for most desktop and mobile GPUs on the market.
Label-set loss functions for partial supervision in image segmentation
[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition
Some experiments with object detection in PyTorch
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
Multi person pose implementation using part affinity fields
Pytorch FPN+ResNet+MaskRCNN Keypoint Detection
pytorch implementation of mask keypoint R-CNN, which is able to detected bbox, keypoints and segmentation.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute
A collection of loss functions for medical image segmentation
A unified framework for machine learning with time series
Object Detection using EfficientNet