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Geometric Capsule Autoencoders for 3D Point Clouds


Russ Salakhutdinov: Capsules may replace ConvNets one day.

1 replies, 304 likes

Nitish Srivastava: Happy to share our recent work, "Geometric Capsule Autoencoders for 3D Point Clouds." The main idea is that instead of finding agreement among parts of an object, we find agreement among different views of the object.

4 replies, 269 likes

Russ Salakhutdinov: New work on Geometric Capsules: Learning to group 3D points into parts & parts into the whole object in unsupervised way. Each capsule represents a visual entity consisting of a pose & feature representing "where" & ''what'' it is. w/t @nitishsr & @Hanlin

0 replies, 141 likes

Hanlin Goh: Check out our latest work on modeling the "what's" and "where's" of objects and parts with geometric capsule representations from 3D point clouds. (with @nitishsr & @rsalakhu)... I'm at #NeurIPS2019 all week if you want to chat about it!

0 replies, 28 likes

Hanlin Goh: Have a look at our recent work with @nitishsr and @rsalakhu on learning geometric capsule representations of objects from 3D point clouds - ... wanna chat about it? Look me up at @NeurIPSConf

1 replies, 15 likes

Antoine Choppin: Reminds me of @JeffCHawkins 's Thousand Brains Theory as he talked about in @lexfridman AI podcast

1 replies, 4 likes

Josh Susskind: Capsules are all you need ;-)

0 replies, 1 likes


Found on Dec 11 2019 at

PDF content of a computer science paper: Geometric Capsule Autoencoders for 3D Point Clouds