3 citations · 5 across the 5 of their papers we have counts for
4 papers
Motion Guided Attention Fusion to Recognize Interactions from Videos
Tae Soo Kim, Jonathan Jones, Gregory D. Hager
We present a dual-pathway approach for recognizing fine-grained interactions from videos. We build on the success of prior dual-stream approaches, but make a distinction between th…
SAFCAR: Structured Attention Fusion for Compositional Action Recognition
Tae Soo Kim, Gregory D. Hager
We present a general framework for compositional action recognition -- i.e. action recognition where the labels are composed out of simpler components such as subjects, atomic-acti…
DASZL: Dynamic Action Signatures for Zero-shot Learning
Tae Soo Kim, Jonathan D. Jones, Michael Peven +6
There are many realistic applications of activity recognition where the set of potential activity descriptions is combinatorially large. This makes end-to-end supervised training o…
Train, Diagnose and Fix: Interpretable Approach for Fine-grained Action Recognition
Jingxuan Hou, Tae Soo Kim, Austin Reiter
Despite the growing discriminative capabilities of modern deep learning methods for recognition tasks, the inner workings of the state-of-art models still remain mostly black-boxes…