research
∙
05/11/2023
Musketeer (All for One, and One for All): A Generalist Vision-Language Model with Task Explanation Prompts
We present a sequence-to-sequence vision-language model whose parameters...
share
research
∙
02/14/2023
PolyFormer: Referring Image Segmentation as Sequential Polygon Generation
In this work, instead of directly predicting the pixel-level segmentatio...
research
∙
08/11/2022
Semi-supervised Vision Transformers at Scale
We study semi-supervised learning (SSL) for vision transformers (ViT), a...
research
∙
08/03/2022
Masked Vision and Language Modeling for Multi-modal Representation Learning
In this paper, we study how to use masked signal modeling in vision and ...
research
∙
07/22/2022
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark
Most existing works on few-shot object detection (FSOD) focus on a setti...
research
∙
04/12/2022
X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks
In this paper, we study the challenging instance-wise vision-language ta...
research
∙
03/30/2022
Omni-DETR: Omni-Supervised Object Detection with Transformers
We consider the problem of omni-supervised object detection, which can u...
research
∙
01/06/2022
Contrastive Neighborhood Alignment
We present Contrastive Neighborhood Alignment (CNA), a manifold learning...
research
∙
01/21/2021
Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning
We present a plug-in replacement for batch normalization (BN) called exp...
research
∙
04/13/2020
Rethinking Differentiable Search for Mixed-Precision Neural Networks
Low-precision networks, with weights and activations quantized to low bi...
research
∙
06/24/2019
Cascade R-CNN: High Quality Object Detection and Instance Segmentation
In object detection, the intersection over union (IoU) threshold is freq...
research
∙
04/09/2019
Towards Universal Object Detection by Domain Attention
Despite increasing efforts on universal representations for visual recog...
research
∙
12/03/2017
Cascade R-CNN: Delving into High Quality Object Detection
In object detection, an intersection over union (IoU) threshold is requi...
research
∙
02/03/2017
Deep Learning with Low Precision by Half-wave Gaussian Quantization
The problem of quantizing the activations of a deep neural network is co...
research
∙
11/13/2015
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking
In recent years, numerous effective multi-object tracking (MOT) methods ...
research
∙
07/19/2015
