26 citations · 59 across the 11 of their papers we have counts for
12 papers
SenseFuse: Label-Free Fusion of Image and Shape Encoders for Open-Vocabulary 3D Instance Segmentation
Euiseok Han, Tri Ton, Hwanhee Kim +2
Open-vocabulary scene understanding is fundamental for robotics, laying the groundwork for spatial reasoning and object manipulation. While closed-vocabulary 3D instance segmentati…
DNI: Dilutional Noise Initialization for Diffusion Video Editing
Sunjae Yoon, Gwanhyeong Koo, Ji Woo Hong +1
Text-based diffusion video editing systems have been successful in performing edits with high fidelity and textual alignment. However, this success is limited to rigid-type editing…
Zero-Shot Dual-Path Integration Framework for Open-Vocabulary 3D Instance Segmentation
Tri Ton, Ji Woo Hong, SooHwan Eom +3
Open-vocabulary 3D instance segmentation transcends traditional closed-vocabulary methods by enabling the identification of both previously seen and unseen objects in real-world sc…
FlexiEdit: Frequency-Aware Latent Refinement for Enhanced Non-Rigid Editing
Gwanhyeong Koo, Sunjae Yoon, Ji Woo Hong +1
Current image editing methods primarily utilize DDIM Inversion, employing a two-branch diffusion approach to preserve the attributes and layout of the original image. However, thes…
FRAG: Frequency Adapting Group for Diffusion Video Editing
Sunjae Yoon, Gwanhyeong Koo, Geonwoo Kim +1
In video editing, the hallmark of a quality edit lies in its consistent and unobtrusive adjustment. Modification, when integrated, must be smooth and subtle, preserving the natural…
Wavelet-Guided Acceleration of Text Inversion in Diffusion-Based Image Editing
Gwanhyeong Koo, Sunjae Yoon, Chang D. Yoo
In the field of image editing, Null-text Inversion (NTI) enables fine-grained editing while preserving the structure of the original image by optimizing null embeddings during the…
Neutral Editing Framework for Diffusion-based Video Editing
Sunjae Yoon, Gwanhyeong Koo, Ji Woo Hong +1
Text-conditioned image editing has succeeded in various types of editing based on a diffusion framework. Unfortunately, this success did not carry over to a video, which continues…
SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation
Hyun Ryu, Sunjae Yoon, Hee Suk Yoon +2
Data augmentation is a crucial component in training neural networks to overcome the limitation imposed by data size, and several techniques have been studied for time series. Alth…
SCANet: Scene Complexity Aware Network for Weakly-Supervised Video Moment Retrieval
Sunjae Yoon, Gwanhyeong Koo, Dahyun Kim +1
Video moment retrieval aims to localize moments in video corresponding to a given language query. To avoid the expensive cost of annotating the temporal moments, weakly-supervised…
ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure
Hee Suk Yoon, Joshua Tian Jin Tee, Eunseop Yoon +4
Studies have shown that modern neural networks tend to be poorly calibrated due to over-confident predictions. Traditionally, post-processing methods have been used to calibrate th…
Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue
Sunjae Yoon, Eunseop Yoon, Hee Suk Yoon +2
Video-grounded Dialogue (VGD) aims to decode an answer sentence to a question regarding a given video and dialogue context. Despite the recent success of multi-modal reasoning to g…
Selective Query-guided Debiasing for Video Corpus Moment Retrieval
Sunjae Yoon, Ji Woo Hong, Eunseop Yoon +4
Video moment retrieval (VMR) aims to localize target moments in untrimmed videos pertinent to a given textual query. Existing retrieval systems tend to rely on retrieval bias as a…