arXiv:2608.21281v1 Announce Type: new
Abstract: Recent advances in field technology have led to a massive influx of in-the-wild video data for ecological science. The primary bottleneck in leveraging...
By Abigail G. Grassick, Jerome Tze-Hou Hsu, Ethan Lin, Ziang Liu, Max Whitton, Madelyn Hair, Liam Gutierrez, Haozheng Yu, Kristin Branson, Vivek Jayaraman, Michael A. Gil, Andrew M. Hein, Jennifer J. Sun
arXiv:2610.29047v1 Announce Type: new
Abstract: Understanding the properties of fish populations is increasingly important. Analyzing fish length, width, and mass is integral to maintaining healthy s...
By Vedanth Kallakuri, Katherine A. Skinner
arXiv:2609.38347v1 Announce Type: new
Abstract: Quantifying collective fish behavior requires accurate trajectories, yet multi-view 3D tracking remains challenging due to frequent occlusions, visuall...
By Patt Phurtivilai, Zhiyang Dou, Yifan Wu, Kinfung Chu, Yuan Liu, Lei Yang, Wenping Wang, Taku Komura
The paper presents the Huntington and Caltech Koi RGB and Sonar dataset (HaCKRS), which pairs Garmin LiveScope imaging-sonar recordings with top‑down RGB video of koi carp. The dataset includes over 105,000 temporally matched frame pairs, spanning about 3.3 hours across four range and orientation configurations, along with detailed metadata, sonar geometry, synchronization data, and planar registration for three horizontal setups. The release focuses on paired observations and calibration to aid annotation and the development of fish detection, tracking, and counting methods, and to explore the use of consumer sonar for ecological monitoring.
By Mourad Derbedrosian, Michael Hobley, Pietro Perona
arXiv:2610.33478v1 Announce Type: cross
Abstract: Marine video understanding is crucial for a wide range of real-world applications. However, existing marine video datasets suffer from limitations, i...
By Quang-Trung Truong, Thanh-Nghia Nguyen, Phu-Phong Vo, Jaeyeon Kim, Cheng Chen, Jie Zhang, Binh-Son Hua, Duc Thanh Nguyen, Ivor Tsang, Sai-Kit Yeung
arXiv:2607. 24064v1 Announce Type: cross Abstract: Recent Vision-Language Models (VLMs) have achieved remarkable success in visual understanding, driven by the growing availability of high-quality image-text pairs.
By Tuan-An To, Yuk-Kwan Wong, Tuan-Anh Vu, Ziqiang Zheng, Sai-Kit Yeung