Indeed, the “dataset issue” is a big challenge against every researcher who takes Computer Vision seriously. There are dozens of problems that remain unanswered, such as: How to build a general image database without bias to purpose? How to create a benchmark that reflects the real-world difficulty of image understanding? How to guarantee the correctness of annotation? etc. The LHI dataset project is started with the surgence of need for better dataset and now, after 2 years, collaboration between a team of 23 full-time labelers at the Lotus Hill Research Institute (LHI), China, and the UCLA Center for Image and Vision Sciences (CIVS) , we have built up the LHI dataset with annotations covering quite broad scope and high accuracy. Although we still don’t have answers to all those questions above, we are stepping toward these directions and doing experiments along the way.

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