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Sangwon Lee's Projects

atss icon atss

Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection, CVPR, Oral, 2020

caffe icon caffe

Caffe: a fast open framework for deep learning.

cgnet icon cgnet

CGNet: A Light-weight Context Guided Network for Semantic Segmentation [arXiv preprint arXiv:1811.08201]

clip icon clip

Contrastive Language-Image Pretraining

connecting_the_dots icon connecting_the_dots

This repository contains the code for the paper "Connecting the Dots: Learning Representations for Active Monocular Depth Estimation" https://avg.is.tuebingen.mpg.de/publications/riegler2019cvpr

detectors icon detectors

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

diffusers icon diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

drit icon drit

Learning diverse image-to-image translation from unpaired data

drit_hr icon drit_hr

Multi-Modal Image-to-Image Translation on Tasks with High-Resolution Images

espnet icon espnet

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

icnet-tensorflow icon icnet-tensorflow

TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".

incubator-mxnet icon incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

isc2021 icon isc2021

Code for the Image similarity challenge.

leeesangwon.github.io icon leeesangwon.github.io

A jekyll theme for the spectral template by html5up.net (@n33co). Demo: http://arkadianriver.github.io/spectral. How to jekyll: http://jekyllrb.com/docs/home/. If you intend to use this theme as a blog site with more than a few pages, have a look at my fork at https://github.com/arkadianriver/arkadianriver.com

mmf icon mmf

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

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