activity
20142023
most citedSimultaneous Detection and Segmentation

198 citations · 802 across the 29 of their papers we have counts for

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19 papers · 1 filter

cs.CV202361 cited

Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles

Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya +10

Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance. While these components lead to effect…

cs.CV2023

Navigating to Objects Specified by Images

Jacob Krantz, Theophile Gervet, Karmesh Yadav +7

Images are a convenient way to specify which particular object instance an embodied agent should navigate to. Solving this task requires semantic visual reasoning and exploration o…

cs.CV20232 cited

Decoupling Human and Camera Motion from Videos in the Wild

Vickie Ye, Georgios Pavlakos, Jitendra Malik +1

We propose a method to reconstruct global human trajectories from videos in the wild. Our optimization method decouples the camera and human motion, which allows us to place people…

cs.CV2021

Tracking People by Predicting 3D Appearance, Location & Pose

Jathushan Rajasegaran, Georgios Pavlakos, Angjoo Kanazawa +1

In this paper, we present an approach for tracking people in monocular videos, by predicting their future 3D representations. To achieve this, we first lift people to 3D from a sin…

cs.CV202110 cited

SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency

Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta +2

In this paper, we explore how we can build upon the data and models of Internet images and use them to adapt to robot vision without requiring any extra labels. We present a framew…

cs.CV202129 cited

MViTv2: Improved Multiscale Vision Transformers for Classification and Detection

Yanghao Li, Chao-Yuan Wu, Haoqi Fan +4

In this paper, we study Multiscale Vision Transformers (MViTv2) as a unified architecture for image and video classification, as well as object detection. We present an improved ve…