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Jihyeon Kim

5 accepted papers

2026

OpenFS: Multi-Hand-Capable Fingerspelling Recognition with Implicit Signing-Hand Detection and Frame-Wise Letter-Conditioned Synthesis

CVPR 2026

Fingerspelling is a component of sign languages in which words are spelled out letter by letter using specific hand poses. Automatic fingerspelling recognition plays a crucial role in bridging the communication gap between Deaf and hearing communities, yet it remains challenging due to the signing-h

Cited by 0SourcecodeScholar
2024

Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy

ICASSP 2024accepted

Class incremental learning aims to solve a problem that arises when continuously adding unseen class instances to an existing model This approach has been extensively studied in the context of image classification; however its applicability to object detection is not well established yet. Existing f…

Cited by 0SourceScholar
2024

SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection

CVPR 2024highlight

In the field of class incremental learning (CIL) generative replay has become increasingly prominent as a method to mitigate the catastrophic forgetting alongside the continuous improvements in generative models. However its application in class incremental object detection (CIOD) has been significa…

Cited by 28SourcePDFScholar
2024

Text2HOI: Text-guided 3D Motion Generation for Hand-Object Interaction

CVPR 2024poster

This paper introduces the first text-guided work for generating the sequence of hand-object interaction in 3D. The main challenge arises from the lack of labeled data where existing ground-truth datasets are nowhere near generalizable in interaction type and object category which inhibits the modeli…

2023

Transformer-Based Unified Recognition of Two Hands Manipulating Objects

CVPR 2023poster

Understanding the hand-object interactions from an egocentric video has received a great attention recently. So far, most approaches are based on the convolutional neural network (CNN) features combined with the temporal encoding via the long short-term memory (LSTM) or graph convolution network (GC…