5 papers
AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models
Zheda Mai, Arpita Chowdhury, Zihe Wang +5
The rise of vision foundation models (VFMs) calls for systematic evaluation. A common approach pairs VFMs with large language models (LLMs) as general-purpose heads, followed by ev…
A Study of Failure Modes in Two-Stage Human-Object Interaction Detection
Lemeng Wang, Qinqian Lei, Vidhi Bakshi +8
Human-object interaction (HOI) detection aims to detect interactions between humans and objects in images. While recent advances have improved performance on existing benchmarks, t…
Lessons and Open Questions from a Unified Study of Camera-Trap Species Recognition Over Time
Sooyoung Jeon, Hongjie Tian, Lemeng Wang +7
Camera traps are vital for large-scale biodiversity monitoring, yet accurate automated analysis remains challenging due to diverse deployment environments. While the computer visio…
Static Segmentation by Tracking: A Label-Efficient Approach for Fine-Grained Specimen Image Segmentation
Zhenyang Feng, Zihe Wang, Jianyang Gu +22
We study image segmentation in the biological domain, particularly trait segmentation from specimen images (e.g., butterfly wing stripes, beetle elytra). This fine-grained task is…
MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs
Jihyung Kil, Zheda Mai, Justin Lee +6
The ability to compare objects, scenes, or situations is crucial for effective decision-making and problem-solving in everyday life. For instance, comparing the freshness of apples…