no code implementations • 20 Dec 2022 • Dipika Singhania, Rahul Rahaman, Angela Yao
For the task of temporal action segmentation, we propose an encoder-decoder-style architecture named C2F-TCN featuring a "coarse-to-fine" ensemble of decoder outputs.
no code implementations • 20 Jul 2022 • Rahul Rahaman, Dipika Singhania, Alexandre Thiery, Angela Yao
In temporal action segmentation, Timestamp supervision requires only a handful of labelled frames per video sequence.
1 code implementation • CVPR 2022 • Fadime Sener, Dibyadip Chatterjee, Daniel Shelepov, Kun He, Dipika Singhania, Robert Wang, Angela Yao
Assembly101 is a new procedural activity dataset featuring 4321 videos of people assembling and disassembling 101 "take-apart" toy vehicles.
1 code implementation • 2 Dec 2021 • Dipika Singhania, Rahul Rahaman, Angela Yao
Our method hinges on unsupervised representation learning, which, for temporal action segmentation, poses unique challenges.
1 code implementation • 23 May 2021 • Dipika Singhania, Rahul Rahaman, Angela Yao
In this work, we propose a novel temporal encoder-decoder to tackle the problem of sequence fragmentation.
Ranked #3 on Action Segmentation on Assembly101
3 code implementations • 22 Jul 2020 • Kamalesh Palanisamy, Dipika Singhania, Angela Yao
Besides, we show that even though we use the pretrained model weights for initialization, there is variance in performance in various output runs of the same model.
Environmental Sound Classification General Classification +2
2 code implementations • ECCV 2020 • Fadime Sener, Dipika Singhania, Angela Yao
Future prediction, especially in long-range videos, requires reasoning from current and past observations.
Ranked #2 on Action Anticipation on Assembly101