1 citations · 4 across the 5 of their papers we have counts for
5 papers
Rethinking Interactive Image Segmentation with Low Latency, High Quality, and Diverse Prompts
Qin Liu, Jaemin Cho, Mohit Bansal +1
The goal of interactive image segmentation is to delineate specific regions within an image via visual or language prompts. Low-latency and high-quality interactive segmentation wi…
SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data
Jialu Li, Jaemin Cho, Yi-Lin Sung +2
Recent text-to-image (T2I) generation models have demonstrated impressive capabilities in creating images from text descriptions. However, these T2I generation models often fall sh…
Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Training
David Wan, Jaemin Cho, Elias Stengel-Eskin +1
Highlighting particularly relevant regions of an image can improve the performance of vision-language models (VLMs) on various vision-language (VL) tasks by guiding the model to at…
Hierarchical Video-Moment Retrieval and Step-Captioning
Abhay Zala, Jaemin Cho, Satwik Kottur +4
There is growing interest in searching for information from large video corpora. Prior works have studied relevant tasks, such as text-based video retrieval, moment retrieval, vide…
MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding
Revanth Gangi Reddy, Xilin Rui, Manling Li +9
Recently, there has been an increasing interest in building question answering (QA) models that reason across multiple modalities, such as text and images. However, QA using images…