26 citations · 32 across the 4 of their papers we have counts for
7 papers · 1 filter
Graph2Vid: Flow graph to Video Grounding for Weakly-supervised Multi-Step Localization
Nikita Dvornik, Isma Hadji, Hai Pham +4
In this work, we consider the problem of weakly-supervised multi-step localization in instructional videos. An established approach to this problem is to rely on a given list of st…
P3IV: Probabilistic Procedure Planning from Instructional Videos with Weak Supervision
He Zhao, Isma Hadji, Nikita Dvornik +3
In this paper, we study the problem of procedure planning in instructional videos. Here, an agent must produce a plausible sequence of actions that can transform the environment fr…
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers
Nikita Dvornik, Isma Hadji, Konstantinos G. Derpanis +2
In this work, we consider the problem of sequence-to-sequence alignment for signals containing outliers. Assuming the absence of outliers, the standard Dynamic Time Warping (DTW) a…
Representation Learning via Global Temporal Alignment and Cycle-Consistency
Isma Hadji, Konstantinos G. Derpanis, Allan D. Jepson
We introduce a weakly supervised method for representation learning based on aligning temporal sequences (e.g., videos) of the same process (e.g., human action). The main idea is t…
Why Convolutional Networks Learn Oriented Bandpass Filters: Theory and Empirical Support
Isma Hadji, Richard P. Wildes
It has been repeatedly observed that convolutional architectures when applied to image understanding tasks learn oriented bandpass filters. A standard explanation of this result is…
What Do We Understand About Convolutional Networks?
Isma Hadji, Richard P. Wildes
This document will review the most prominent proposals using multilayer convolutional architectures. Importantly, the various components of a typical convolutional network will be…