activity
20192022
most citedActivity Graph Transformer for Temporal Action Localization

42 citations · 45 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2022

Rethinking Learning Approaches for Long-Term Action Anticipation

Megha Nawhal, Akash Abdu Jyothi, Greg Mori

Action anticipation involves predicting future actions having observed the initial portion of a video. Typically, the observed video is processed as a whole to obtain a video-level…

cs.CV2021

Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation

Mengyao Zhai, Lei Chen, Jiawei He +3

Humans accumulate knowledge in a lifelong fashion. Modern deep neural networks, on the other hand, are susceptible to catastrophic forgetting: when adapted to perform new tasks, th…

cs.CV202142 cited

Activity Graph Transformer for Temporal Action Localization

Megha Nawhal, Greg Mori

We introduce Activity Graph Transformer, an end-to-end learnable model for temporal action localization, that receives a video as input and directly predicts a set of action instan…

cs.CV2020

MCMI: Multi-Cycle Image Translation with Mutual Information Constraints

Xiang Xu, Megha Nawhal, Greg Mori +1

We present a mutual information-based framework for unsupervised image-to-image translation. Our MCMI approach treats single-cycle image translation models as modules that can be u…

cs.CV2019

Generating Videos of Zero-Shot Compositions of Actions and Objects

Megha Nawhal, Mengyao Zhai, Andreas Lehrmann +2

Human activity videos involve rich, varied interactions between people and objects. In this paper we develop methods for generating such videos -- making progress toward addressing…

cs.LG20193 cited

Continuous Graph Flow

Zhiwei Deng, Megha Nawhal, Lili Meng +1

In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the mode…