BioVL-QR: Egocentric Biochemical Vision-and-Language Dataset Using Micro QR Codes
원문 초록
This paper introduces BioVL-QR, a biochemical vision-and-language dataset comprising 23 egocentric experiment videos, corresponding protocols, and vision-and-language alignments. A major challenge in understanding biochemical videos is detecting equipment, reagents, and containers because of the cluttered environment and indistinguishable objects. Previous studies assumed manual object annotation, which is costly and time-consuming. To address the issue, we focus on Micro QR Codes. However, detecting objects using only Micro QR Codes is still difficult due to blur and occlusion caused by object manipulation. To overcome this, we propose an object labeling method combining a Micro QR Code detector with an off-the-shelf hand object detector. As an application of the method and BioVL-QR, we tackled the task of localizing the procedural steps in an instructional video. The experimental results show that using Micro QR Codes and our method improves biochemical video understanding. Data and code are available through https://nishi10mo.github.io/BioVL-QR/
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
InterRVOS: Interaction-aware Referring Video Object Segmentation
UGC-VideoCaptioner: An Omni UGC Video Detail Caption Model and New Benchmarks
RoHOI: Robustness Benchmark for Human-Object Interaction Detection
Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework
MCAM: Multimodal Causal Analysis Model for Ego-Vehicle-Level Driving Video Understanding
Omni-Video: Democratizing Unified Video Understanding and Generation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.