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06/14/2023
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement
We present a novel model for Tracking Any Point (TAP) that effectively t...
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05/23/2023
Perception Test: A Diagnostic Benchmark for Multimodal Video Models
We propose a novel multimodal video benchmark - the Perception Test - to...
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01/23/2023
Zorro: the masked multimodal transformer
Attention-based models are appealing for multimodal processing because i...
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11/07/2022
TAP-Vid: A Benchmark for Tracking Any Point in a Video
Generic motion understanding from video involves not only tracking objec...
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10/12/2022
Self-supervised video pretraining yields strong image representations
Videos contain far more information than still images and hold the poten...
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10/06/2022
Compressed Vision for Efficient Video Understanding
Experience and reasoning occur across multiple temporal scales: millisec...
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09/30/2022
Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods
Self-supervised methods have achieved remarkable success in transfer lea...
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03/17/2022
Transframer: Arbitrary Frame Prediction with Generative Models
We present a general-purpose framework for image modelling and vision ta...
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03/16/2022
Object discovery and representation networks
The promise of self-supervised learning (SSL) is to leverage large amoun...
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02/22/2022
Hierarchical Perceiver
General perception systems such as Perceivers can process arbitrary moda...
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02/15/2022
General-purpose, long-context autoregressive modeling with Perceiver AR
Real-world data is high-dimensional: a book, image, or musical performan...
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12/06/2021
Input-level Inductive Biases for 3D Reconstruction
Much of the recent progress in 3D vision has been driven by the developm...
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11/23/2021
Towards Learning Universal Audio Representations
The ability to learn universal audio representations that can solve dive...
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07/30/2021
Perceiver IO: A General Architecture for Structured Inputs Outputs
The recently-proposed Perceiver model obtains good results on several do...
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03/19/2021
Efficient Visual Pretraining with Contrastive Detection
Self-supervised pretraining has been shown to yield powerful representat...
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03/04/2021
Perceiver: General Perception with Iterative Attention
Biological systems understand the world by simultaneously processing hig...
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10/21/2020
A Short Note on the Kinetics-700-2020 Human Action Dataset
We describe the 2020 edition of the DeepMind Kinetics human action datas...
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05/01/2020
The AVA-Kinetics Localized Human Actions Video Dataset
This paper describes the AVA-Kinetics localized human actions video data...
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03/11/2020
Visual Grounding in Video for Unsupervised Word Translation
There are thousands of actively spoken languages on Earth, but a single ...
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10/24/2019
Controllable Attention for Structured Layered Video Decomposition
The objective of this paper is to be able to separate a video into its n...
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07/15/2019
A Short Note on the Kinetics-700 Human Action Dataset
We describe an extension of the DeepMind Kinetics human action dataset f...
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02/09/2019
Cloud Programming Simplified: A Berkeley View on Serverless Computing
Serverless cloud computing handles virtually all the system administrati...
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12/06/2018
Video Action Transformer Network
We introduce the Action Transformer model for recognizing and localizing...
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12/04/2018
The Visual Centrifuge: Model-Free Layered Video Representations
True video understanding requires making sense of non-lambertian scenes ...
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08/03/2018
A Short Note about Kinetics-600
We describe an extension of the DeepMind Kinetics human action dataset f...
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07/26/2018
A Better Baseline for AVA
We introduce a simple baseline for action localization on the AVA datase...
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06/11/2018
Massively Parallel Video Networks
We introduce a class of causal video understanding models that aims to i...
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05/22/2017
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
The paucity of videos in current action classification datasets (UCF-101...
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05/19/2017
The Kinetics Human Action Video Dataset
We describe the DeepMind Kinetics human action video dataset. The datase...
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07/23/2015
Human Pose Estimation with Iterative Error Feedback
Hierarchical feature extractors such as Convolutional Networks (ConvNets...
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05/07/2015
Learning to See by Moving
The dominant paradigm for feature learning in computer vision relies on ...
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05/01/2015
Pose Induction for Novel Object Categories
We address the task of predicting pose for objects of unannotated object...
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03/22/2015
Lifting Object Detection Datasets into 3D
While data has certainly taken the center stage in computer vision in re...
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11/22/2014
Virtual View Networks for Object Reconstruction
All that structure from motion algorithms "see" are sets of 2D points. W...
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11/22/2014
Category-Specific Object Reconstruction from a Single Image
Object reconstruction from a single image -- in the wild -- is a problem...
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09/24/2010
