Moon Ye-Bin

According to our database, Moon Ye-Bin authored at least 8 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

ENInst: Enhancing weakly-supervised low-shot instance segmentation.

Moon Ye-Bin, Dongmin Choi, Yongjin Kwon, Junsik Kim, Tae-Hyun Oh

Pattern Recognit., January, 2024

VLM's Eye Examination: Instruct and Inspect Visual Competency of Vision Language Models.

Nam Hyeon-Woo, Moon Ye-Bin, Won-Seok Choi, Lee Hyun, Tae-Hyun Oh

CoRR, 2024

BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-Language Models.

Moon Ye-Bin, Nam Hyeon-Woo, Wonseok Choi, Tae-Hyun Oh

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Exploiting Synthetic Data for Data Imbalance Problems: Baselines from a Data Perspective.

Moon Ye-Bin, Nam Hyeon-Woo, Wonseok Choi, Nayeong Kim, Suha Kwak, Tae-Hyun Oh

CoRR, 2023

TextManiA: Enriching Visual Feature by Text-driven Manifold Augmentation.

Moon Ye-Bin, Jisoo Kim, Hongyeob Kim, Kilho Son, Tae-Hyun Oh

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning.

Nam Hyeon-Woo, Moon Ye-Bin, Tae-Hyun Oh

Proceedings of the Tenth International Conference on Learning Representations, 2022

HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields.

Kim Jun-Seong, Kim Yu-Ji, Moon Ye-Bin, Tae-Hyun Oh

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

FedPara: Low-rank Hadamard Product Parameterization for Efficient Federated Learning.

Nam Hyeon-Woo, Moon Ye-Bin, Tae-Hyun Oh

CoRR, 2021