These graphs are for the IEEE/CVF Conference on Computer Vision and Pattern Recognition. The top graph is a visualization on the main conference papers for the conference distributed based on their similarity to each other. The closer the papers are, the more similar the abstracts. This graph can be used to search for papers and to find papers that are similar to each other. Once you find an interesting paper by searching, you can hover your mouse over nearby papers to see them. You can also click and drag a box over the graph to see common words in the abstracts and list of the papers on the right.

Each dot represents a paper with the color representing the subject area (legend below this graph). The papers are arranged by a measure of similarity.

If you hover over a dot, you see the related paper.

If you click on a dot, you go to the related paper page.

You can search for papers by author, subject area, or title

Drag a rectangle to summarize an area of the plot.

Graphs created by Dr. Christopher Funk (Kitware). Special thanks to Dr. Roni Choudhury (Kitware) for helping make the graphs for CVPR 2020, Dr. Hendrik Strobelt (IBM) for the original similarity graph created for Mini-Conf, Professor Sasha Rush (Cornell) for advice on the embeddings, and Dr. Anthony Hoogs (Kitware) and Dr. Jeffrey Baumes (Kitware) for support and advice.