research
∙
09/21/2023
Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features
The rapid development of 3D object detection systems for self-driving ca...
share
research
∙
09/05/2023
Doppelgangers: Learning to Disambiguate Images of Similar Structures
We consider the visual disambiguation task of determining whether a pair...
research
∙
06/08/2023
Tracking Everything Everywhere All at Once
We present a new test-time optimization method for estimating dense and ...
research
∙
06/06/2023
Emergent Correspondence from Image Diffusion
Finding correspondences between images is a fundamental problem in compu...
research
∙
04/24/2023
Distilling from Similar Tasks for Transfer Learning on a Budget
We address the challenge of getting efficient yet accurate recognition s...
research
∙
03/27/2023
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving
For a self-driving car to operate reliably, its perceptual system must g...
research
∙
02/09/2023
Polynomial Neural Fields for Subband Decomposition and Manipulation
Neural fields have emerged as a new paradigm for representing signals, t...
research
∙
09/23/2022
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs
A self-driving car must be able to reliably handle adverse weather condi...
research
∙
08/01/2022
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions
Advances in perception for self-driving cars have accelerated in recent ...
research
∙
07/07/2022
Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners
Few-shot recognition involves training an image classifier to distinguis...
research
∙
04/14/2022
Activation Regression for Continuous Domain Generalization with Applications to Crop Classification
Geographic variance in satellite imagery impacts the ability of machine ...
research
∙
03/29/2022
Learning to Detect Mobile Objects from LiDAR Scans Without Labels
Current 3D object detectors for autonomous driving are almost entirely t...
research
∙
03/23/2022
Visual Prompt Tuning
The current modus operandi in adapting pre-trained models involves updat...
research
∙
03/22/2022
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception
Self-driving cars must detect vehicles, pedestrians, and other traffic p...
research
∙
03/16/2022
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
Unsupervised semantic segmentation aims to discover and localize semanti...
research
∙
02/26/2022
Orientation-Discriminative Feature Representation for Decentralized Pedestrian Tracking
This paper focuses on the problem of decentralized pedestrian tracking u...
research
∙
02/01/2022
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
In applications such as optical see-through and projector augmented real...
research
∙
08/24/2021
Field-Guide-Inspired Zero-Shot Learning
Modern recognition systems require large amounts of supervision to achie...
research
∙
04/28/2021
Extreme Rotation Estimation using Dense Correlation Volumes
We present a technique for estimating the relative 3D rotation of an RGB...
research
∙
03/30/2021
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering
We present a new framework for semantic segmentation without annotations...
research
∙
03/26/2021
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection
Self-driving cars must detect other vehicles and pedestrians in 3D to pl...
research
∙
12/02/2020
Fine-Grained Few-Shot Classification with Feature Map Reconstruction Networks
In this paper we reformulate few-shot classification as a reconstruction...
research
∙
11/25/2020
Augmentation-Interpolative AutoEncoders for Unsupervised Few-Shot Image Generation
We aim to build image generation models that generalize to new domains f...
research
∙
10/15/2020
Self-training for Few-shot Transfer Across Extreme Task Differences
All few-shot learning techniques must be pre-trained on a large, labeled...
research
∙
08/14/2020
Learning Gradient Fields for Shape Generation
In this work, we propose a novel technique to generate shapes from point...
research
∙
07/06/2020
Wasserstein Distances for Stereo Disparity Estimation
Existing approaches to depth or disparity estimation output a distributi...
research
∙
05/17/2020
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
In the domain of autonomous driving, deep learning has substantially imp...
research
∙
04/28/2020
Learning Feature Descriptors using Camera Pose Supervision
Recent research on learned visual descriptors has shown promising improv...
research
∙
04/26/2020
Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset
In this work we explore the task of instance segmentation with attribute...
research
∙
04/24/2020
Extending and Analyzing Self-Supervised Learning Across Domains
Self-supervised representation learning has achieved impressive results ...
research
∙
04/07/2020
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
Reliable and accurate 3D object detection is a necessity for safe autono...
research
∙
04/01/2020
Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition
Few-shot, fine-grained classification requires a model to learn subtle, ...
research
∙
10/30/2019
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images
Object segmentation in three-dimensional (3-D) point clouds is a critica...
research
∙
10/08/2019
When Does Self-supervision Improve Few-shot Learning?
We present a technique to improve the generalization of deep representat...
research
∙
10/03/2019
On the Efficacy of Knowledge Distillation
In this paper, we present a thorough evaluation of the efficacy of knowl...
research
∙
09/03/2019
Few-Shot Generalization for Single-Image 3D Reconstruction via Priors
Recent work on single-view 3D reconstruction shows impressive results, b...
research
∙
08/29/2019
GeoStyle: Discovering Fashion Trends and Events
Understanding fashion styles and trends is of great potential interest t...
research
∙
06/28/2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
As 3D point clouds become the representation of choice for multiple visi...
research
∙
06/17/2019
Boosting Supervision with Self-Supervision for Few-shot Learning
We present a technique to improve the transferability of deep representa...
research
∙
06/14/2019
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Detecting objects such as cars and pedestrians in 3D plays an indispensa...
research
∙
04/09/2019
Few-Shot Learning with Localization in Realistic Settings
Traditional recognition methods typically require large, artificially-ba...
research
∙
12/18/2018
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
3D object detection is an essential task in autonomous driving. Recent t...
research
∙
10/24/2018
A Deep-Learning-Based Fashion Attributes Detection Model
Analyzing fashion attributes is essential in the fashion design process....
research
∙
10/03/2018
Deep Fundamental Matrix Estimation without Correspondences
Estimating fundamental matrices is a classic problem in computer vision....
research
∙
05/22/2018
Resource Aware Person Re-identification across Multiple Resolutions
Not all people are equally easy to identify: color statistics might be e...
research
∙
01/16/2018
Low-Shot Learning from Imaginary Data
Humans can quickly learn new visual concepts, perhaps because they can e...
research
∙
06/07/2017
Low-shot learning with large-scale diffusion
This paper considers the problem of inferring image labels for which onl...
research
∙
05/10/2017
Inferring and Executing Programs for Visual Reasoning
Existing methods for visual reasoning attempt to directly map inputs to ...
research
∙
12/20/2016
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
When building artificial intelligence systems that can reason and answer...
research
∙
12/19/2016