Search Results for author: Jaeyoung Yoo

Found 9 papers, 2 papers with code

Coreset Selection for Object Detection

no code implementations14 Apr 2024 Hojun Lee, Suyoung Kim, JunHoo Lee, Jaeyoung Yoo, Nojun Kwak

Coreset selection is a method for selecting a small, representative subset of an entire dataset.

Image Classification Object +2

MDPose: Real-Time Multi-Person Pose Estimation via Mixture Density Model

no code implementations17 Feb 2023 Seunghyeon Seo, Jaeyoung Yoo, Jihye Hwang, Nojun Kwak

In this work, we propose a novel framework of single-stage instance-aware pose estimation by modeling the joint distribution of human keypoints with a mixture density model, termed as MDPose.

Keypoint Estimation Multi-Person Pose Estimation

End-to-End Multi-Object Detection with a Regularized Mixture Model

no code implementations18 May 2022 Jaeyoung Yoo, Hojun Lee, Seunghyeon Seo, Inseop Chung, Nojun Kwak

Recent end-to-end multi-object detectors simplify the inference pipeline by removing hand-crafted processes such as non-maximum suppression (NMS).

Density Estimation Object +2

MatteFormer: Transformer-Based Image Matting via Prior-Tokens

1 code implementation CVPR 2022 Gyutae Park, Sungjoon Son, Jaeyoung Yoo, SeHo Kim, Nojun Kwak

In this paper, we propose a transformer-based image matting model called MatteFormer, which takes full advantage of trimap information in the transformer block.

Image Matting

KL-Divergence-Based Region Proposal Network for Object Detection

no code implementations22 May 2020 Geonseok Seo, Jaeyoung Yoo, Jae-Seok Choi, Nojun Kwak

The learning of the region proposal in object detection using the deep neural networks (DNN) is divided into two tasks: binary classification and bounding box regression task.

Binary Classification Object +3

Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image

3 code implementations ICCV 2021 Jaeyoung Yoo, Hojun Lee, Inseop Chung, Geonseok Seo, Nojun Kwak

Instead of assigning each ground truth to specific locations of network's output, we train a network by estimating the probability density of bounding boxes in an input image using a mixture model.

Density Estimation Object +2

Unpriortized Autoencoder For Image Generation

no code implementations12 Feb 2019 Jaeyoung Yoo, Hojun Lee, Nojun Kwak

In this paper, we treat the image generation task using an autoencoder, a representative latent model.

Density Estimation Image Generation +1

Vehicle Image Generation Going Well with The Surroundings

no code implementations9 Jul 2018 Jeesoo Kim, Jangho Kim, Jaeyoung Yoo, Daesik Kim, Nojun Kwak

Using a subnetwork based on a precedent work of image completion, our model makes the shape of an object.

Colorization Image Generation +7

Image Restoration by Estimating Frequency Distribution of Local Patches

no code implementations CVPR 2018 Jaeyoung Yoo, Sang-ho Lee, Nojun Kwak

In this paper, we propose a method to solve the image restoration problem, which tries to restore the details of a corrupted image, especially due to the loss caused by JPEG compression.

General Classification Image Compression +1

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