14 citations · 14 across the 2 of their papers we have counts for
6 papers · 1 filter
PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding
Jang Hyun Cho, Andrea Madotto, Effrosyni Mavroudi +26
Vision-language models are integral to computer vision research, yet many high-performing models remain closed-source, obscuring their data, design and training recipe. The researc…
Collecting Consistently High Quality Object Tracks with Minimal Human Involvement by Using Self-Supervised Learning to Detect Tracker Errors
Samreen Anjum, Suyog Jain, Danna Gurari
We propose a hybrid framework for consistently producing high-quality object tracks by combining an automated object tracker with little human input. The key idea is to tailor a mo…
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…
Predicting How to Distribute Work Between Algorithms and Humans to Segment an Image Batch
Danna Gurari, Yinan Zhao, Suyog Dutt Jain +2
Foreground object segmentation is a critical step for many image analysis tasks. While automated methods can produce high-quality results, their failures disappoint users in need o…
Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos
Bo Xiong, Suyog Dutt Jain, Kristen Grauman
We propose an end-to-end learning framework for segmenting generic objects in both images and videos. Given a novel image or video, our approach produces a pixel-level mask for all…
Click Carving: Segmenting Objects in Video with Point Clicks
Suyog Dutt Jain, Kristen Grauman
We present a novel form of interactive video object segmentation where a few clicks by the user helps the system produce a full spatio-temporal segmentation of the object of intere…