50 citations · 246 across the 33 of their papers we have counts for
37 papers · 1 filter
Semantics-Guided Object Removal for Facial Images: with Broad Applicability and Robust Style Preservation
Jookyung Song, Yeonjin Chang, Seonguk Park +1
Object removal and image inpainting in facial images is a task in which objects that occlude a facial image are specifically targeted, removed, and replaced by a properly reconstru…
Imposing Consistency for Optical Flow Estimation
Jisoo Jeong, Jamie Menjay Lin, Fatih Porikli +1
Imposing consistency through proxy tasks has been shown to enhance data-driven learning and enable self-supervision in various tasks. This paper introduces novel and effective cons…
MatteFormer: Transformer-Based Image Matting via Prior-Tokens
GyuTae Park, SungJoon Son, JaeYoung Yoo +2
In this paper, we propose a transformer-based image matting model called MatteFormer, which takes full advantage of trimap information in the transformer block. Our method first in…
Exploiting Inter-pixel Correlations in Unsupervised Domain Adaptation for Semantic Segmentation
Inseop Chung, Jayeon Yoo, Nojun Kwak
"Self-training" has become a dominant method for semantic segmentation via unsupervised domain adaptation (UDA). It creates a set of pseudo labels for the target domain to give exp…
Few-Shot Object Detection by Attending to Per-Sample-Prototype
Hojun Lee, Myunggi Lee, Nojun Kwak
Few-shot object detection aims to detect instances of specific categories in a query image with only a handful of support samples. Although this takes less effort than obtaining en…
Normalization Matters in Weakly Supervised Object Localization
Jeesoo Kim, Junsuk Choe, Sangdoo Yun +1
Weakly-supervised object localization (WSOL) enables finding an object using a dataset without any localization information. By simply training a classification model using only im…