Shu Kong | Computer Vision Lab

We release our developed benchmarking protocols and datasets that have supported our research projects. See details by navigating the links below.

	Data retrieved from LAION-400M to study Retrieval-based Augmented Learning (RAL)
	A High-Resolution for Instance Detection with Multi-View Instance Capture
	Dataset to Study Instance Tracking in 3D Scenes from Egocentric Videos
	A Benchmark to Study Few-Shot Detection from Annotation Guidelines
	Data to Study Unstructured Unlabeled Optical Motion Capture
	AccessDB: A Dataset for Auto-detecting Inaccessibility of Everyday Objects
	A Benchmark to Study Long-Tailed 3D Detection
	UAL-Bench: A Benchmark for Unusual Activity Localization in Videos
	Dataset for Shoeprint Identification in Crime Scenes
	Dataset for Open-Vocabulary Part Segmentation
	Dataset for Image Aesthetics Rating
	Dataset for Fossil Pollen Recognition
	Dataset for C. elegans segmentation, body shape estimation, and age estimation
	Dataset for Pollen Grain Detection