78 citations · 149 across the 16 of their papers we have counts for
16 papers
General Item Representation Learning for Cold-start Content Recommendations
Jooeun Kim, Jinri Kim, Kwangeun Yeo +4
Cold-start item recommendation is a long-standing challenge in recommendation systems. A common remedy is to use a content-based approach, but rich information from raw contents in…
Learning Pseudo-Labeler beyond Noun Concepts for Open-Vocabulary Object Detection
Sunghun Kang, Junbum Cha, Jonghwan Mun +2
Open-vocabulary object detection (OVOD) has recently gained significant attention as a crucial step toward achieving human-like visual intelligence. Existing OVOD methods extend ta…
Honeybee: Locality-enhanced Projector for Multimodal LLM
Junbum Cha, Wooyoung Kang, Jonghwan Mun +1
In Multimodal Large Language Models (MLLMs), a visual projector plays a crucial role in bridging pre-trained vision encoders with LLMs, enabling profound visual understanding while…
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning
Taehoon Kim, Pyunghwan Ahn, Sangyun Kim +39
In this report, we introduce NICE (New frontiers for zero-shot Image Captioning Evaluation) project and share the results and outcomes of 2023 challenge. This project is designed t…
Noise-aware Learning from Web-crawled Image-Text Data for Image Captioning
Wooyoung Kang, Jonghwan Mun, Sungjun Lee +1
Image captioning is one of the straightforward tasks that can take advantage of large-scale web-crawled data which provides rich knowledge about the visual world for a captioning m…
Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
Junbum Cha, Jonghwan Mun, Byungseok Roh
We tackle open-world semantic segmentation, which aims at learning to segment arbitrary visual concepts in images, by using only image-text pairs without dense annotations. Existin…