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11/18/2022
Magic3D: High-Resolution Text-to-3D Content Creation
DreamFusion has recently demonstrated the utility of a pre-trained text-...
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08/11/2022
Optimizing Anchor-based Detectors for Autonomous Driving Scenes
This paper summarizes model improvements and inference-time optimization...
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07/12/2022
Vision Transformer for NeRF-Based View Synthesis from a Single Input Image
Although neural radiance fields (NeRF) have shown impressive advances fo...
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06/15/2022
A Unified Sequence Interface for Vision Tasks
While language tasks are naturally expressed in a single, unified, model...
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03/03/2022
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields
Thin, reflective objects such as forks and whisks are common in our dail...
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12/22/2021
Open-Vocabulary Image Segmentation
We design an open-vocabulary image segmentation model to organize an ima...
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12/17/2021
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation
This work presents a simple vision transformer design as a strong baseli...
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08/25/2021
Multi-Task Self-Training for Learning General Representations
Despite the fast progress in training specialized models for various tas...
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08/20/2021
Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image
3D perception of object shapes from RGB image input is fundamental towar...
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08/15/2021
Learning Open-World Object Proposals without Learning to Classify
Object proposals have become an integral preprocessing steps of many vis...
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07/01/2021
Learning to See before Learning to Act: Visual Pre-training for Manipulation
Does having visual priors (e.g. the ability to detect objects) facilitat...
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06/30/2021
Simple Training Strategies and Model Scaling for Object Detection
The speed-accuracy Pareto curve of object detection systems have advance...
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06/25/2021
Single Image Texture Translation for Data Augmentation
Recent advances in image synthesis enables one to translate images by le...
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04/28/2021
Zero-Shot Detection via Vision and Language Knowledge Distillation
Zero-shot image classification has made promising progress by training t...
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03/13/2021
Revisiting ResNets: Improved Training and Scaling Strategies
Novel computer vision architectures monopolize the spotlight, but the im...
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01/27/2021
Bottleneck Transformers for Visual Recognition
We present BoTNet, a conceptually simple yet powerful backbone architect...
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12/13/2020
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
Building instance segmentation models that are data-efficient and can ha...
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12/10/2020
iNeRF: Inverting Neural Radiance Fields for Pose Estimation
We present iNeRF, a framework that performs pose estimation by "invertin...
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10/22/2020
Efficient Scale-Permuted Backbone with Learned Resource Distribution
Recently, SpineNet has demonstrated promising results on object detectio...
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07/26/2020
Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve
Object recognition has seen significant progress in the image domain, wi...
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06/11/2020
Rethinking Pre-training and Self-training
Pre-training is a dominant paradigm in computer vision. For example, sup...
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04/11/2020
Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos
We leverage unsupervised learning of depth, egomotion, and camera intrin...
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12/10/2019
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
Convolutional neural networks typically encode an input image into a ser...
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12/02/2019
MnasFPN: Learning Latency-aware Pyramid Architecture for Object Detection on Mobile Devices
Despite the blooming success of architecture search for vision tasks in ...
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06/26/2019
Learning Data Augmentation Strategies for Object Detection
Data augmentation is a critical component of training deep learning mode...
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04/16/2019
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection
Current state-of-the-art convolutional architectures for object detectio...
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04/05/2019
ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors
Instance segmentation aims to detect and segment individual objects in a...
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01/16/2019
Class-Balanced Loss Based on Effective Number of Samples
With the rapid increase of large-scale, real-world datasets, it becomes ...
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10/30/2018
DropBlock: A regularization method for convolutional networks
Deep neural networks often work well when they are over-parameterized an...
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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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12/09/2016
Feature Pyramid Networks for Object Detection
Feature pyramids are a basic component in recognition systems for detect...
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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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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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05/01/2014
