3 citations · 23 across the 66 of their papers we have counts for
9 papers · 1 filter
Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation
Atin Pothiraj, Jaemin Cho, Yue Zhang +2
Video generation models are increasingly capable of producing realistic videos, but they still struggle to generate videos that follow basic physical laws. Compounding this is a la…
Does AI See like Art Historians? Interpreting How Vision Language Models Recognize Artistic Style
Marvin Limpijankit, Milad Alshomary, Yassin Oulad Daoud +9
VLMs have become increasingly proficient at a range of computer vision tasks, such as visual question answering and object detection. This includes increasingly strong capabilities…
PoSh: Using Scene Graphs To Guide LLMs-as-a-Judge For Detailed Image Descriptions
Amith Ananthram, Elias Stengel-Eskin, Lorena A. Bradford +7
While vision-language models (VLMs) have advanced into detailed image description, evaluation remains a challenge. Standard metrics (e.g. CIDEr, SPICE) were designed for short text…
RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation
Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin +1
We investigate to what extent Multimodal Large Language Models (MLLMs) can accurately identify the orientation of input images rotated 0°, 90°, 180°, and 270°. This task demands ro…
How Well Do Vision-Language Models Understand Movies?
Emmanouil Zaranis, António Farinhas, Saul Santos +28
Vision-language models (VLMs) can increasingly handle extended contexts and answer questions about long videos--but can they understand the narrative structure of movies as humans…
CLaMR: Contextualized Late-Interaction for Multimodal Content Retrieval
David Wan, Han Wang, Elias Stengel-Eskin +2
Online video web content is richly multimodal: a single video blends vision, speech, ambient audio, and on-screen text. Retrieval systems typically treat these modalities as indepe…
CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
Atin Pothiraj, Elias Stengel-Eskin, Jaemin Cho +1
Recognizing and reasoning about occluded (partially or fully hidden) objects is vital to understanding visual scenes, as occlusions frequently occur in real-world environments and…
VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos
Ziyang Wang, Shoubin Yu, Elias Stengel-Eskin +4
Long-form video understanding is complicated by the high redundancy of video data and the abundance of query-irrelevant information. To tackle these challenges, we propose VideoTre…
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…