activity
20152023
most citedLearning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

517 citations · 746 across the 18 of their papers we have counts for

collaborators

18 papers

cs.CV2023

Variational Distribution Learning for Unsupervised Text-to-Image Generation

Minsoo Kang, Doyup Lee, Jiseob Kim +2

We propose a text-to-image generation algorithm based on deep neural networks when text captions for images are unavailable during training. In this work, instead of simply generat…

cs.CV2022

Generalizable Implicit Neural Representations via Instance Pattern Composers

Chiheon Kim, Doyup Lee, Saehoon Kim +2

Despite recent advances in implicit neural representations (INRs), it remains challenging for a coordinate-based multi-layer perceptron (MLP) of INRs to learn a common representati…

cs.CV2022★ 6 cited

Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer

Doyup Lee, Chiheon Kim, Saehoon Kim +2

Although autoregressive models have achieved promising results on image generation, their unidirectional generation process prevents the resultant images from fully reflecting glob…

cs.CV2022★ 10 cited

Autoregressive Image Generation using Residual Quantization

Doyup Lee, Chiheon Kim, Saehoon Kim +2

For autoregressive (AR) modeling of high-resolution images, vector quantization (VQ) represents an image as a sequence of discrete codes. A short sequence length is important for a…

cs.CV2021★ 92 cited

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

Byungseok Roh, JaeWoong Shin, Wuhyun Shin +1

DETR is the first end-to-end object detector using a transformer encoder-decoder architecture and demonstrates competitive performance but low computational efficiency on high reso…

cs.LG2021★ 8 cited

Automated Learning Rate Scheduler for Large-batch Training

Chiheon Kim, Saehoon Kim, Jongmin Kim +2

Large-batch training has been essential in leveraging large-scale datasets and models in deep learning. While it is computationally beneficial to use large batch sizes, it often re…