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05/03/2023
Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime
Large-scale visual language models are widely used as pre-trained models...
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03/23/2023
Three ways to improve feature alignment for open vocabulary detection
The core problem in zero-shot open vocabulary detection is how to align ...
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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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11/24/2022
Multi-Task Learning of Object State Changes from Uncurated Videos
We aim to learn to temporally localize object state changes and the corr...
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04/29/2022
Flamingo: a Visual Language Model for Few-Shot Learning
Building models that can be rapidly adapted to numerous tasks using only...
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03/22/2022
Look for the Change: Learning Object States and State-Modifying Actions from Untrimmed Web Videos
Human actions often induce changes of object states such as "cutting an ...
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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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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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05/01/2021
Generative Art Using Neural Visual Grammars and Dual Encoders
Whilst there are perhaps only a few scientific methods, there seem to be...
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04/26/2021
Multimodal Self-Supervised Learning of General Audio Representations
We present a multimodal framework to learn general audio representations...
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04/12/2021
Machine Translation Decoding beyond Beam Search
Beam search is the go-to method for decoding auto-regressive machine tra...
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03/30/2021
Broaden Your Views for Self-Supervised Video Learning
Most successful self-supervised learning methods are trained to align th...
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03/30/2021
Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers
Our objective is language-based search of large-scale image and video da...
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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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01/31/2021
Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers
Recently multimodal transformer models have gained popularity because th...
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08/03/2020
RareAct: A video dataset of unusual interactions
This paper introduces a manually annotated video dataset of unusual acti...
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06/29/2020
Self-Supervised MultiModal Versatile Networks
Videos are a rich source of multi-modal supervision. In this work, we le...
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05/07/2020
Learning to Segment Actions from Observation and Narration
We apply a generative segmental model of task structure, guided by narra...
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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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12/13/2019
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Annotating videos is cumbersome, expensive and not scalable. Yet, many s...
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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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06/07/2019
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips
Learning text-video embeddings usually requires a dataset of video clips...
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05/31/2019
Are Labels Required for Improving Adversarial Robustness?
Recent work has uncovered the interesting (and somewhat surprising) find...
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03/19/2019
Cross-task weakly supervised learning from instructional videos
In this paper we investigate learning visual models for the steps of ord...
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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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09/22/2018
Learning to Localize and Align Fine-Grained Actions to Sparse Instructions
Automatic generation of textual video descriptions that are time-aligned...
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06/29/2018
A flexible model for training action localization with varying levels of supervision
Spatio-temporal action detection in videos is typically addressed in a f...
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07/27/2017
Learning from Video and Text via Large-Scale Discriminative Clustering
Discriminative clustering has been successfully applied to a number of w...
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06/14/2017
SEARNN: Training RNNs with Global-Local Losses
We propose SEARNN, a novel training algorithm for recurrent neural netwo...
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02/09/2017
Joint Discovery of Object States and Manipulation Actions
Many human activities involve object manipulations aiming to modify the ...
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05/30/2016
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
In this paper, we propose several improvements on the block-coordinate F...
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06/30/2015
