This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
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Updated
Jul 24, 2024 - Python
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
CVNets: A library for training computer vision networks
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h). This is an official implementation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
This is an official implementation for "Contextual Transformer Networks for Visual Recognition".
This repository contains the source code of our work on designing efficient CNNs for computer vision
VarifocalNet: An IoU-aware Dense Object Detector
The official repo for [NeurIPS'21] "ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias" and [IJCV'22] "ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond"
SWA Object Detection
Official ImageNet Model repository
Video Platform for Action Recognition and Object Detection in Pytorch
[ECCV 2020] Boundary-preserving Mask R-CNN
Semantic Propositional Image Caption Evaluation
High-resolution Networks for the Fully Convolutional One-Stage Object Detection (FCOS) algorithm
generate captions for images using a CNN-RNN model that is trained on the Microsoft Common Objects in COntext (MS COCO) dataset
A tensorflow implement mobilenetv3 centernet, which can be easily deployeed on android(MNN) and ios(CoreML).
A repository and interchange format for weed identification annotation
A tool for converting computer vision label formats.
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