10 citations · 31 across the 12 of their papers we have counts for
12 papers
EventCoT: Event-centric Video Chain-of-thought for Reasoning Temporal Localization
Youngkil Song, Yoonjae Baek, Dongwon Kim +3
Reasoning temporal localization (RTL) requires a model to generate an answer that itself contains the time interval supporting it, coupling high-level reasoning with temporal groun…
ACID: Action Consistency via Inverse Dynamics for Planning with World Models
Gawon Seo, Dongwon Kim, Suha Kwak
Decision-time planning with action-conditioned world models has become a popular paradigm for embodied control. However, the standard planning cost judges a candidate solely by how…
Improving Text-based Person Search via Part-level Cross-modal Correspondence
Jicheol Park, Boseung Jeong, Dongwon Kim +1
Text-based person search is the task of finding person images that are the most relevant to the natural language text description given as query. The main challenge of this task is…
Bootstrapping Top-down Information for Self-modulating Slot Attention
Dongwon Kim, Seoyeon Kim, Suha Kwak
Object-centric learning (OCL) aims to learn representations of individual objects within visual scenes without manual supervision, facilitating efficient and effective visual reaso…
PLOT: Text-based Person Search with Part Slot Attention for Corresponding Part Discovery
Jicheol Park, Dongwon Kim, Boseung Jeong +1
Text-based person search, employing free-form text queries to identify individuals within a vast image collection, presents a unique challenge in aligning visual and textual repres…
Shatter and Gather: Learning Referring Image Segmentation with Text Supervision
Dongwon Kim, Namyup Kim, Cuiling Lan +1
Referring image segmentation, the task of segmenting any arbitrary entities described in free-form texts, opens up a variety of vision applications. However, manual labeling of tra…
Extending CLIP's Image-Text Alignment to Referring Image Segmentation
Seoyeon Kim, Minguk Kang, Dongwon Kim +2
Referring Image Segmentation (RIS) is a cross-modal task that aims to segment an instance described by a natural language expression. Recent methods leverage large-scale pretrained…
Improving Cross-Modal Retrieval with Set of Diverse Embeddings
Dongwon Kim, Namyup Kim, Suha Kwak
Cross-modal retrieval across image and text modalities is a challenging task due to its inherent ambiguity: An image often exhibits various situations, and a caption can be coupled…
Self-Taught Metric Learning without Labels
Sungyeon Kim, Dongwon Kim, Minsu Cho +1
We present a novel self-taught framework for unsupervised metric learning, which alternates between predicting class-equivalence relations between data through a moving average of…
ReSTR: Convolution-free Referring Image Segmentation Using Transformers
Namyup Kim, Dongwon Kim, Cuiling Lan +2
Referring image segmentation is an advanced semantic segmentation task where target is not a predefined class but is described in natural language. Most of existing methods for thi…
Embedding Transfer with Label Relaxation for Improved Metric Learning
Sungyeon Kim, Dongwon Kim, Minsu Cho +1
This paper presents a novel method for embedding transfer, a task of transferring knowledge of a learned embedding model to another. Our method exploits pairwise similarities betwe…
Proxy Anchor Loss for Deep Metric Learning
Sungyeon Kim, Dongwon Kim, Minsu Cho +1
Existing metric learning losses can be categorized into two classes: pair-based and proxy-based losses. The former class can leverage fine-grained semantic relations between data p…