activity
20132023
most citedFoveaBox: Beyond Anchor-based Object Detector

940 citations · 1.4k across the 43 of their papers we have counts for

collaborators
Showing 2016Show all

6 papers · 1 filter

cs.CV2016★ 8 cited

Social Behavior Prediction from First Person Videos

Shan Su, Jung Pyo Hong, Jianbo Shi +1

This paper presents a method to predict the future movements (location and gaze direction) of basketball players as a whole from their first person videos. The predicted behaviors…

cs.CV2016

Am I a Baller? Basketball Performance Assessment from First-Person Videos

Gedas Bertasius, Hyun Soo Park, Stella X. Yu +1

This paper presents a method to assess a basketball player's performance from his/her first-person video. A key challenge lies in the fact that the evaluation metric is highly subj…

cs.CV2016★ 2 cited

Unsupervised Learning of Important Objects from First-Person Videos

Gedas Bertasius, Hyun Soo Park, Stella X. Yu +1

A first-person camera, placed at a person's head, captures, which objects are important to the camera wearer. Most prior methods for this task learn to detect such important object…

cs.CV2016★ 1 cited

Local Perturb-and-MAP for Structured Prediction

Gedas Bertasius, Qiang Liu, Lorenzo Torresani +1

Conditional random fields (CRFs) provide a powerful tool for structured prediction, but cast significant challenges in both the learning and inference steps. Approximation techniqu…

cs.CV2016★ 14 cited

Convolutional Random Walk Networks for Semantic Image Segmentation

Gedas Bertasius, Lorenzo Torresani, Stella X. Yu +1

Most current semantic segmentation methods rely on fully convolutional networks (FCNs). However, their use of large receptive fields and many pooling layers cause low spatial resol…

cs.CV2016★ 16 cited

First Person Action-Object Detection with EgoNet

Gedas Bertasius, Hyun Soo Park, Stella X. Yu +1

Unlike traditional third-person cameras mounted on robots, a first-person camera, captures a person's visual sensorimotor object interactions from up close. In this paper, we study…