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04/05/2023
Segment Anything
We introduce the Segment Anything (SA) project: a new task, model, and d...
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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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01/20/2022
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
Model pre-training is a cornerstone of modern visual recognition systems...
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11/22/2021
Benchmarking Detection Transfer Learning with Vision Transformers
Object detection is a central downstream task used to test if pre-traine...
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11/11/2021
Masked Autoencoders Are Scalable Vision Learners
This paper shows that masked autoencoders (MAE) are scalable self-superv...
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06/28/2021
Early Convolutions Help Transformers See Better
Vision transformer (ViT) models exhibit substandard optimizability. In p...
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03/30/2021
Boundary IoU: Improving Object-Centric Image Segmentation Evaluation
We present Boundary IoU (Intersection-over-Union), a new segmentation ev...
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03/11/2021
Fast and Accurate Model Scaling
In this work we analyze strategies for convolutional neural network scal...
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02/01/2021
Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details
By design, average precision (AP) for object detection aims to treat all...
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03/30/2020
Designing Network Design Spaces
In this work, we present a new network design paradigm. Our goal is to h...
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03/26/2020
Are Labels Necessary for Neural Architecture Search?
Existing neural network architectures in computer vision — whether desig...
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08/08/2019
LVIS: A Dataset for Large Vocabulary Instance Segmentation
Progress on object detection is enabled by datasets that focus the resea...
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05/30/2019
On Network Design Spaces for Visual Recognition
Over the past several years progress in designing better neural network ...
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03/28/2019
TensorMask: A Foundation for Dense Object Segmentation
Sliding-window object detectors that generate bounding-box object predic...
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01/08/2019
Panoptic Feature Pyramid Networks
The recently introduced panoptic segmentation task has renewed our commu...
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11/21/2018
Rethinking ImageNet Pre-training
We report competitive results on object detection and instance segmentat...
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01/03/2018
Panoptic Segmentation
We propose and study a novel 'Panoptic Segmentation' (PS) task. Panoptic...
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12/12/2017
Data Distillation: Towards Omni-Supervised Learning
We investigate omni-supervised learning, a special regime of semi-superv...
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11/28/2017
Learning to Segment Every Thing
Existing methods for object instance segmentation require all training i...
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08/07/2017
Focal Loss for Dense Object Detection
The highest accuracy object detectors to date are based on a two-stage a...
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06/08/2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Deep learning thrives with large neural networks and large datasets. How...
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03/20/2017
Mask R-CNN
We present a conceptually simple, flexible, and general framework for ob...
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12/19/2016
Learning Features by Watching Objects Move
This paper presents a novel yet intuitive approach to unsupervised featu...
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12/09/2016
Feature Pyramid Networks for Object Detection
Feature pyramids are a basic component in recognition systems for detect...
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11/16/2016
Aggregated Residual Transformations for Deep Neural Networks
We present a simple, highly modularized network architecture for image c...
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04/07/2016
A MultiPath Network for Object Detection
The recent COCO object detection dataset presents several new challenges...
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03/29/2016
Learning to Refine Object Segments
Object segmentation requires both object-level information and low-level...
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11/18/2015
Metric Learning with Adaptive Density Discrimination
Distance metric learning (DML) approaches learn a transformation to a re...
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11/13/2015
Unsupervised Learning of Edges
Data-driven approaches for edge detection have proven effective and achi...
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09/04/2015
Semantic Amodal Segmentation
Common visual recognition tasks such as classification, object detection...
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06/20/2015
Learning to Segment Object Candidates
Recent object detection systems rely on two critical steps: (1) a set of...
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04/01/2015
Microsoft COCO Captions: Data Collection and Evaluation Server
In this paper we describe the Microsoft COCO Caption dataset and evaluat...
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02/17/2015
What makes for effective detection proposals?
Current top performing object detectors employ detection proposals to gu...
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11/18/2014
From Captions to Visual Concepts and Back
This paper presents a novel approach for automatically generating image ...
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06/20/2014
Fast Edge Detection Using Structured Forests
Edge detection is a critical component of many vision systems, including...
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06/04/2014
Local Decorrelation For Improved Detection
Even with the advent of more sophisticated, data-hungry methods, boosted...
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05/27/2014
Layered Logic Classifiers: Exploring the `And' and `Or' Relations
Designing effective and efficient classifier for pattern analysis is a k...
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05/01/2014