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20212024
most citedHigh-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions

4 citations · 17 across the 12 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 2 cited

StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On

Jeongho Kim, Gyojung Gu, Minho Park +2

Given a clothing image and a person image, an image-based virtual try-on aims to generate a customized image that appears natural and accurately reflects the characteristics of the…

cs.CV2023

Expression Domain Translation Network for Cross-domain Head Reenactment

Taewoong Kang, Jeongsik Oh, Jaeseong Lee +2

Despite the remarkable advancements in head reenactment, the existing methods face challenges in cross-domain head reenactment, which aims to transfer human motions to domains outs…

cs.CV2023★ 1 cited

Label Shift Adapter for Test-Time Adaptation under Covariate and Label Shifts

Sunghyun Park, Seunghan Yang, Jaegul Choo +1

Test-time adaptation (TTA) aims to adapt a pre-trained model to the target domain in a batch-by-batch manner during inference. While label distributions often exhibit imbalances in…

cs.CV2023★ 3 cited

Reference-based Image Composition with Sketch via Structure-aware Diffusion Model

Kangyeol Kim, Sunghyun Park, Junsoo Lee +1

Recent remarkable improvements in large-scale text-to-image generative models have shown promising results in generating high-fidelity images. To further enhance editability and en…

cs.CV2023★ 1 cited

Improving Scene Text Recognition for Character-Level Long-Tailed Distribution

Sunghyun Park, Sunghyo Chung, Jungsoo Lee +1

Despite the recent remarkable improvements in scene text recognition (STR), the majority of the studies focused mainly on the English language, which only includes few number of ch…

cs.CV2023

RobustSwap: A Simple yet Robust Face Swapping Model against Attribute Leakage

Jaeseong Lee, Taewoo Kim, Sunghyun Park +2

Face swapping aims at injecting a source image's identity (i.e., facial features) into a target image, while strictly preserving the target's attributes, which are irrelevant to id…