activity
20152022
most citedPosition, Padding and Predictions: A Deeper Look at Position Information in CNNs

42 citations · 156 across the 15 of their papers we have counts for

collaborators
Showing cs.CVShow all

19 papers · 1 filter

cs.CV20224 cited

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…

cs.CV20228 cited

Semantic keypoint-based pose estimation from single RGB frames

Karl Schmeckpeper, Philip R. Osteen, Yufu Wang +6

This paper presents an approach to estimating the continuous 6-DoF pose of an object from a single RGB image. The approach combines semantic keypoints predicted by a convolutional…

cs.CV2021

Simpler Does It: Generating Semantic Labels with Objectness Guidance

Md Amirul Islam, Matthew Kowal, Sen Jia +2

Existing weakly or semi-supervised semantic segmentation methods utilize image or box-level supervision to generate pseudo-labels for weakly labeled images. However, due to the lac…

cs.CV202126 cited

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…

cs.CV2021

SegMix: Co-occurrence Driven Mixup for Semantic Segmentation and Adversarial Robustness

Md Amirul Islam, Matthew Kowal, Konstantinos G. Derpanis +1

In this paper, we present a strategy for training convolutional neural networks to effectively resolve interference arising from competing hypotheses relating to inter-categorical…

cs.CV2021

Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs

Md Amirul Islam, Matthew Kowal, Sen Jia +2

In this paper, we challenge the common assumption that collapsing the spatial dimensions of a 3D (spatial-channel) tensor in a convolutional neural network (CNN) into a vector via…