This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.

Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.

1st solution for the Webly-supervised Fine-grained Recognition competition in https://www.cvmart.net/race/10412/base

provide some new architecture, channel pruning and quantization methods for yolov5

Pytorch implementation of some vision transformers, trained on CIFAR-10.

Official PyTorch Code for Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation: Solution for FeTS 2022 Task 2

Master: Meta Style Transformer for Controllable Zero-Shot and Few-Shot Artistic Style Transfer

Project for coding information into images via teganography and cryptography.

Swin backbone for UNet network for semantic segmentation

A Swin Transformer equivalent for 3D sparse volumes

This Repo contains code for used for age and gender detection in CCTV videos

Java Gui ile veritabanına bağlanan kullanıcı kaydı uygulaması

The initial stage of this work focuses on creating a segmented image from a given satellite image with different classes. In the second stage, these images should be converted to an ABM-friendly format. At the final stage, they can be used to simulate the real-world environment with related agents using a suitable Agent-based model.

M.Sc Lab Code