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06/01/2023
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles
Modern hierarchical vision transformers have added several vision-specif...
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04/06/2023
Diffusion Models as Masked Autoencoders
There has been a longstanding belief that generation can facilitate a tr...
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03/23/2023
The effectiveness of MAE pre-pretraining for billion-scale pretraining
This paper revisits the standard pretrain-then-finetune paradigm used in...
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12/15/2022
MAViL: Masked Audio-Video Learners
We present Masked Audio-Video Learners (MAViL) to train audio-visual rep...
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12/01/2022
Scaling Language-Image Pre-training via Masking
We present Fast Language-Image Pre-training (FLIP), a simple and more ef...
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11/18/2022
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference
Vision Transformers (ViTs) have shown impressive performance but still r...
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05/18/2022
Masked Autoencoders As Spatiotemporal Learners
This paper studies a conceptually simple extension of Masked Autoencoder...
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04/01/2022
On the Importance of Asymmetry for Siamese Representation Learning
Many recent self-supervised frameworks for visual representation learnin...
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03/29/2022
Unified Transformer Tracker for Object Tracking
As an important area in computer vision, object tracking has formed two ...
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01/20/2022
MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video Recognition
While today's video recognition systems parse snapshots or short clips a...
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12/16/2021
Masked Feature Prediction for Self-Supervised Visual Pre-Training
We present Masked Feature Prediction (MaskFeat) for self-supervised pre-...
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12/02/2021
Improved Multiscale Vision Transformers for Classification and Detection
In this paper, we study Multiscale Vision Transformers (MViT) as a unifi...
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11/18/2021
PyTorchVideo: A Deep Learning Library for Video Understanding
We introduce PyTorchVideo, an open-source deep-learning library that pro...
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04/29/2021
A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
We present a large-scale study on unsupervised spatiotemporal representa...
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04/22/2021
Multiscale Vision Transformers
We present Multiscale Vision Transformers (MViT) for video and image rec...
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04/02/2021
Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories
The standard way of training video models entails sampling at each itera...
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04/01/2021
Multiview Pseudo-Labeling for Semi-supervised Learning from Video
We present a multiview pseudo-labeling approach to video learning, a nov...
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03/28/2021
HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval
Video-Text Retrieval has been a hot research topic with the explosion of...
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11/25/2020
Can Temporal Information Help with Contrastive Self-Supervised Learning?
Leveraging temporal information has been regarded as essential for devel...
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03/09/2020
Improved Baselines with Momentum Contrastive Learning
Contrastive unsupervised learning has recently shown encouraging progres...
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11/13/2019
Momentum Contrast for Unsupervised Visual Representation Learning
We present Momentum Contrast (MoCo) for unsupervised visual representati...
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12/12/2018
Long-Term Feature Banks for Detailed Video Understanding
To understand the world, we humans constantly need to relate the present...
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12/10/2018
SlowFast Networks for Video Recognition
We present SlowFast networks for video recognition. Our model involves (...
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10/06/2017