4 citations · 5 across the 19 of their papers we have counts for
20 papers
HumanSkill-4D: Training-Free Language Querying of Animatable Gaussian Avatars in Space and Time
Junsu Kim, unsu Kim, Naeun Kim +2
We introduce avatar referring segmentation, which selects regions of animatable Gaussian avatars from language queries. A query can also specify a pose or motion to select matching…
3rd Place Solution to Human Motion Challenges in Real-World and Clinical Settings (MoCha) @ECCV2026: Language-Aligned Motion Representations for Domain-Generalizable UPDRS-Gait Severity Estimation
Soojie Kim, Muhammad Munsif, Minkyung Kim +1
In this work, we introduce language-aligned motion representations for domain-generalizable UPDRS-Gait severity estimation, aiming to learn semantically structured motion features…
Where Is the Bee? Detecting Tiny Pollinators with a Single Collaborative-Head Transformer
Junsu Kim, Seungryul Baek
The CVPPA@ECCV 2026 BuzzSpot Challenge asks us to detect bees, bumblebees, hoverflies, and moths in 1920x1080 field keyframes. Its annotations carry 2 difficulties: the median box…
Local K-Similarity Constraint for Federated Learning with Label Noise
Sanskar Amgain, Prashant Shrestha, Bidur Khanal +5
Federated learning on clients with noisy labels is a challenging problem, as such clients can infiltrate the global model, impacting the overall generalizability of the system. Exi…
Can Synthetic Images Conquer Forgetting? Beyond Unexplored Doubts in Few-Shot Class-Incremental Learning
Junsu Kim, Yunhoe Ku, Seungryul Baek
Few-shot class-incremental learning (FSCIL) is challenging due to extremely limited training data; while aiming to reduce catastrophic forgetting and learn new information. We prop…
Revisiting Reliability in the Reasoning-based Pose Estimation Benchmark
Junsu Kim, Naeun Kim, Jaeho Lee +3
The reasoning-based pose estimation (RPE) benchmark has emerged as a widely adopted evaluation standard for pose-aware multimodal large language models (MLLMs). Despite its signifi…
Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detection
Taehoon Kim, Jongwook Choi, Yonghyun Jeong +4
We introduce a deepfake video detection approach that exploits pixel-wise temporal inconsistencies, which traditional spatial frequency-based detectors often overlook. Traditional…
BIGS: Bimanual Category-agnostic Interaction Reconstruction from Monocular Videos via 3D Gaussian Splatting
Jeongwan On, Kyeonghwan Gwak, Gunyoung Kang +4
Reconstructing 3Ds of hand-object interaction (HOI) is a fundamental problem that can find numerous applications. Despite recent advances, there is no comprehensive pipeline yet fo…
Beyond Synthetic Replays: Turning Diffusion Features into Few-Shot Class-Incremental Learning Knowledge
Junsu Kim, Yunhoe Ku, Dongyoon Han +1
Few-shot class-incremental learning (FSCIL) is challenging due to extremely limited training data while requiring models to acquire new knowledge without catastrophic forgetting. R…
QORT-Former: Query-optimized Real-time Transformer for Understanding Two Hands Manipulating Objects
Elkhan Ismayilzada, MD Khalequzzaman Chowdhury Sayem, Yihalem Yimolal Tiruneh +3
Significant advancements have been achieved in the realm of understanding poses and interactions of two hands manipulating an object. The emergence of augmented reality (AR) and vi…
Leveraging 2D Masked Reconstruction for Domain Adaptation of 3D Pose Estimation
Hansoo Park, Chanwoo Kim, Jihyeon Kim +4
RGB-based 3D pose estimation methods have been successful with the development of deep learning and the emergence of high-quality 3D pose datasets. However, most existing methods d…
EmoTalkingGaussian: Continuous Emotion-conditioned Talking Head Synthesis
Junuk Cha, Seongro Yoon, Valeriya Strizhkova +2
3D Gaussian splatting-based talking head synthesis has recently gained attention for its ability to render high-fidelity images with real-time inference speed. However, since it is…
B-RIGHT: Benchmark Re-evaluation for Integrity in Generalized Human-Object Interaction Testing
Yoojin Jang, Junsu Kim, Hayeon Kim +4
Human-object interaction (HOI) is an essential problem in artificial intelligence (AI) which aims to understand the visual world that involves complex relationships between humans…
Text2Relight: Creative Portrait Relighting with Text Guidance
Junuk Cha, Mengwei Ren, Krishna Kumar Singh +6
We present a lighting-aware image editing pipeline that, given a portrait image and a text prompt, performs single image relighting. Our model modifies the lighting and color of bo…
1st Place Solution to the 8th HANDS Workshop Challenge -- ARCTIC Track: 3DGS-based Bimanual Category-agnostic Interaction Reconstruction
Jeongwan On, Kyeonghwan Gwak, Gunyoung Kang +5
This report describes our 1st place solution to the 8th HANDS workshop challenge (ARCTIC track) in conjunction with ECCV 2024. In this challenge, we address the task of bimanual ca…
Text2HOI: Text-guided 3D Motion Generation for Hand-Object Interaction
Junuk Cha, Jihyeon Kim, Jae Shin Yoon +1
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 existin…
Exploiting Style Latent Flows for Generalizing Deepfake Video Detection
Jongwook Choi, Taehoon Kim, Yonghyun Jeong +2
This paper presents a new approach for the detection of fake videos, based on the analysis of style latent vectors and their abnormal behavior in temporal changes in the generated…
VLM-PL: Advanced Pseudo Labeling Approach for Class Incremental Object Detection via Vision-Language Model
Junsu Kim, Yunhoe Ku, Jihyeon Kim +2
In the field of Class Incremental Object Detection (CIOD), creating models that can continuously learn like humans is a major challenge. Pseudo-labeling methods, although initially…
SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection
Junsu Kim, Hoseong Cho, Jihyeon Kim +2
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…
Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy
Junsu Kim, Sumin Hong, Chanwoo Kim +6
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 th…