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08/28/2023
VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation
Existing approaches to unsupervised video instance segmentation typicall...
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06/13/2023
GeneCIS: A Benchmark for General Conditional Image Similarity
We argue that there are many notions of 'similarity' and that models, li...
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05/09/2023
ImageBind: One Embedding Space To Bind Them All
We present ImageBind, an approach to learn a joint embedding across six ...
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04/14/2023
DINOv2: Learning Robust Visual Features without Supervision
The recent breakthroughs in natural language processing for model pretra...
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04/11/2023
MOST: Multiple Object localization with Self-supervised Transformers for object discovery
We tackle the challenging task of unsupervised object localization in th...
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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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02/28/2023
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
Semi-supervised learning aims to train a model using limited labels. Sta...
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01/26/2023
Cut and Learn for Unsupervised Object Detection and Instance Segmentation
We propose Cut-and-LEaRn (CutLER), a simple approach for training unsupe...
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01/26/2023
Vision-Language Models Performing Zero-Shot Tasks Exhibit Gender-based Disparities
We explore the extent to which zero-shot vision-language models exhibit ...
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01/23/2023
A Simple Recipe for Competitive Low-compute Self supervised Vision Models
Self-supervised methods in vision have been mostly focused on large arch...
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01/19/2023
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
This paper demonstrates an approach for learning highly semantic image r...
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10/13/2022
The Hidden Uniform Cluster Prior in Self-Supervised Learning
A successful paradigm in representation learning is to perform self-supe...
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06/16/2022
OmniMAE: Single Model Masked Pretraining on Images and Videos
Transformer-based architectures have become competitive across a variety...
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04/14/2022
Masked Siamese Networks for Label-Efficient Learning
We propose Masked Siamese Networks (MSN), a self-supervised learning fra...
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02/16/2022
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Discriminative self-supervised learning allows training models on any ra...
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02/16/2022
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments
Data-Augmentation (DA) is known to improve performance across tasks and ...
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01/20/2022
Omnivore: A Single Model for Many Visual Modalities
Prior work has studied different visual modalities in isolation and deve...
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01/07/2022
Detecting Twenty-thousand Classes using Image-level Supervision
Current object detectors are limited in vocabulary size due to the small...
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12/20/2021
Mask2Former for Video Instance Segmentation
We find Mask2Former also achieves state-of-the-art performance on video ...
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12/02/2021
Masked-attention Mask Transformer for Universal Image Segmentation
Image segmentation is about grouping pixels with different semantics, e....
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09/16/2021
An End-to-End Transformer Model for 3D Object Detection
We propose 3DETR, an end-to-end Transformer based object detection model...
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05/13/2021
3D Spatial Recognition without Spatially Labeled 3D
We introduce WyPR, a Weakly-supervised framework for Point cloud Recogni...
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04/29/2021
Emerging Properties in Self-Supervised Vision Transformers
In this paper, we question if self-supervised learning provides new prop...
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04/28/2021
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples
This paper proposes a novel method of learning by predicting view assign...
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04/26/2021
MDETR – Modulated Detection for End-to-End Multi-Modal Understanding
Multi-modal reasoning systems rely on a pre-trained object detector to e...
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03/29/2021
Robust Audio-Visual Instance Discrimination
We present a self-supervised learning method to learn audio and video re...
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03/18/2021
Space-Time Crop Attend: Improving Cross-modal Video Representation Learning
The quality of the image representations obtained from self-supervised l...
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03/02/2021
Self-supervised Pretraining of Visual Features in the Wild
Recently, self-supervised learning methods like MoCo, SimCLR, BYOL and S...
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01/07/2021
Self-Supervised Pretraining of 3D Features on any Point-Cloud
Pretraining on large labeled datasets is a prerequisite to achieve good ...
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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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06/17/2020
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Unsupervised image representations have significantly reduced the gap wi...
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04/27/2020
Audio-Visual Instance Discrimination with Cross-Modal Agreement
We present a self-supervised learning approach to learn audio-visual rep...
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01/10/2020
In Defense of Grid Features for Visual Question Answering
Popularized as 'bottom-up' attention, bounding box (or region) based vis...
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12/06/2019
ClusterFit: Improving Generalization of Visual Representations
Pre-training convolutional neural networks with weakly-supervised and se...
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12/04/2019
Self-Supervised Learning of Pretext-Invariant Representations
The goal of self-supervised learning from images is to construct image r...
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06/06/2019
3D-RelNet: Joint Object and Relational Network for 3D Prediction
We propose an approach to predict the 3D shape and pose for the objects ...
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06/06/2019
Does Object Recognition Work for Everyone?
The paper analyzes the accuracy of publicly available object-recognition...
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05/03/2019
Scaling and Benchmarking Self-Supervised Visual Representation Learning
Self-supervised learning aims to learn representations from the data its...
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01/19/2019
Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding
Providing systems the ability to relate linguistic and visual content is...
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12/04/2017
Learning by Asking Questions
We introduce an interactive learning framework for the development and t...
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08/04/2017
Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
A major impediment in rapidly deploying object detection models for inst...
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04/13/2016
Visual Storytelling
We introduce the first dataset for sequential vision-to-language, and ex...
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04/12/2016
Cross-stitch Networks for Multi-task Learning
Multi-task learning in Convolutional Networks has displayed remarkable s...
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03/28/2016
Shuffle and Learn: Unsupervised Learning using Temporal Order Verification
In this paper, we present an approach for learning a visual representati...
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03/19/2016
Generating Natural Questions About an Image
There has been an explosion of work in the vision & language community d...
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12/22/2015