Seonghoon-Yu's repositories

AI_Paper_Review

까먹으면 다시 보려고 정리합니다.

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Zero-shot-RIS

[CVPR 2023] Official code for "Zero-shot Referring Image Segmentation with Global-Local Context Features"

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MoCov2_Pytorch_tutorial

MoCo v2 Pytorch tutorial, https://arxiv.org/abs/2003.04297

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Pseudo-RIS

[ECCV 2024] Official code for "Pseudo-RIS: Distinctive Pseudo-supervision Generation for Referring Image Segmentation"

Data-structure-and-Algorithm

공부 목적으로 자료 구조와 알고리즘을 파이썬으로 구현해보고 있습니다.

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Awesome-Referring-Image-Segmentation

:books: A collection of papers about Referring Image Segmentation.

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ISLR-Python

ISLR(An Introduction to Statistical Learning) 공부 과정을 기록하는 저장소 입니다.

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leetcode

파이썬 알고리즘 인터뷰를 공부하면서 leetcode 문제 풀이 코드를 정리해보았습니다.

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Machine-Learning-Collection

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

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PyTorch-RetinaNet-from-scratch

Google Colab 환경에서 RetinaNet을 PyTorch로 바닥부터 구현합니다.

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PyTorch_study

PyTorch Computer Vision Cookbook를 공부한 내용을 정리하는 저장소입니다.

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Awesome-Video-Captioning

A curated list of research papers in Video Captioning

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CaGNet-Zero-Shot-Semantic-Segmentation

Code for our ACMMM2020 paper "Context-aware Feature Generation for Zero-shot Semantic Segmentation".

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denseclip

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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OWOCR

성장을 위한 1주 1코드리뷰하는 레포지토리 입니다.

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GIST-Creative-and-Self-motivating-Project

GIST 창의자율 프로젝트

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JoEm

An official implementation of "Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation" (ICCV 2021) in PyTorch.

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LISA

Project Page for "LISA: Reasoning Segmentation via Large Language Model"

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NPSN

Official Code for "Non-Probability Sampling Network for Stochastic Human Trajectory Prediction (CVPR 2022)"

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Paper-review-for-CV-SSL

Paper review for Computer Vision and Self-Supervised Learning

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pytorch-retinanet

RetinaNet in PyTorch

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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