517 citations · 880 across the 52 of their papers we have counts for
7 papers · 1 filter
ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation
Dayoung Gong, Suha Kwak, Minsu Cho
Temporal action segmentation and long-term action anticipation are two popular vision tasks for the temporal analysis of actions in videos. Despite apparent relevance and potential…
Efficient and Versatile Robust Fine-Tuning of Zero-shot Models
Sungyeon Kim, Boseung Jeong, Donghyun Kim +1
Large-scale image-text pre-trained models enable zero-shot classification and provide consistent accuracy across various data distributions. Nonetheless, optimizing these models in…
Online Temporal Action Localization with Memory-Augmented Transformer
Youngkil Song, Dongkeun Kim, Minsu Cho +1
Online temporal action localization (On-TAL) is the task of identifying multiple action instances given a streaming video. Since existing methods take as input only a video segment…
FREST: Feature RESToration for Semantic Segmentation under Multiple Adverse Conditions
Sohyun Lee, Namyup Kim, Sungyeon Kim +1
Robust semantic segmentation under adverse conditions is crucial in real-world applications. To address this challenging task in practical scenarios where labeled normal condition…
Classification Matters: Improving Video Action Detection with Class-Specific Attention
Jinsung Lee, Taeoh Kim, Inwoong Lee +4
Video action detection (VAD) aims to detect actors and classify their actions in a video. We figure that VAD suffers more from classification rather than localization of actors. He…
Extreme Point Supervised Instance Segmentation
Hyeonjun Lee, Sehyun Hwang, Suha Kwak
This paper introduces a novel approach to learning instance segmentation using extreme points, i.e., the topmost, leftmost, bottommost, and rightmost points, of each object. These…
Active Label Correction for Semantic Segmentation with Foundation Models
Hoyoung Kim, Sehyun Hwang, Suha Kwak +1
Training and validating models for semantic segmentation require datasets with pixel-wise annotations, which are notoriously labor-intensive. Although useful priors such as foundat…