activity
20182021
most cited3D Human Pose Estimation from Deep Multi-View 2D Pose

11 citations · 16 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Self-Denoising Neural Networks for Few Shot Learning

Steven Schwarcz, Sai Saketh Rambhatla, Rama Chellappa

In this paper, we introduce a new architecture for few shot learning, the task of teaching a neural network from as few as one or five labeled examples. Inspired by the theoretical…

cs.CV2021

Finding Facial Forgery Artifacts with Parts-Based Detectors

Steven Schwarcz, Rama Chellappa

Manipulated videos, especially those where the identity of an individual has been modified using deep neural networks, are becoming an increasingly relevant threat in the modern da…

cs.CV20195 cited

SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong

Steven Schwarcz, Peng Xu, David D'Ambrosio +4

We introduce a new high resolution, high frame rate stereo video dataset, which we call SPIN, for tracking and action recognition in the game of ping pong. The corpus consists of p…

cs.CV201911 cited

3D Human Pose Estimation from Deep Multi-View 2D Pose

Steven Schwarcz, Thomas Pollard

Human pose estimation - the process of recognizing a human's limb positions and orientations in a video - has many important applications including surveillance, diagnosis of movem…

cs.CV2018

A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos

Joshua Gleason, Rajeev Ranjan, Steven Schwarcz +3

Existing approaches for spatio-temporal action detection in videos are limited by the spatial extent and temporal duration of the actions. In this paper, we present a modular syste…