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09/20/2023
COSE: A Consistency-Sensitivity Metric for Saliency on Image Classification
We present a set of metrics that utilize vision priors to effectively as...
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06/08/2023
LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs
A critical obstacle preventing NeRF models from being deployed broadly i...
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06/05/2023
DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling
Many modern applications use computer vision to detect and count objects...
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12/13/2022
Accidental Turntables: Learning 3D Pose by Watching Objects Turn
We propose a technique for learning single-view 3D object pose estimatio...
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08/18/2022
MvDeCor: Multi-view Dense Correspondence Learning for Fine-grained 3D Segmentation
We propose to utilize self-supervised techniques in the 2D domain for fi...
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07/24/2022
Cross-Modal 3D Shape Generation and Manipulation
Creating and editing the shape and color of 3D objects require tremendou...
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04/11/2022
Improving Few-Shot Part Segmentation using Coarse Supervision
A significant bottleneck in training deep networks for part segmentation...
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03/22/2022
Leveraging Textures in Zero-shot Understanding of Fine-Grained Domains
Textures can be used to describe the appearance of objects in a wide ran...
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12/01/2021
GANORCON: Are Generative Models Useful for Few-shot Segmentation?
Advances in generative modeling based on GANs has motivated the communit...
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11/23/2021
Semi-Supervised Learning with Taxonomic Labels
We propose techniques to incorporate coarse taxonomic labels to train im...
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08/03/2021
Domain Adaptor Networks for Hyperspectral Image Recognition
We consider the problem of adapting a network trained on three-channel c...
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07/02/2021
On Measuring and Controlling the Spectral Bias of the Deep Image Prior
The deep image prior has demonstrated the remarkable ability that untrai...
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06/02/2021
The Semi-Supervised iNaturalist Challenge at the FGVC8 Workshop
Semi-iNat is a challenging dataset for semi-supervised classification wi...
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04/01/2021
A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification
We evaluate the effectiveness of semi-supervised learning (SSL) on a rea...
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03/11/2021
The Semi-Supervised iNaturalist-Aves Challenge at FGVC7 Workshop
This document describes the details and the motivation behind a new data...
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01/26/2021
Revisiting Contrastive Learning for Few-Shot Classification
Instance discrimination based contrastive learning has emerged as a lead...
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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...
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12/16/2020
StarcNet: Machine Learning for Star Cluster Identification
We present a machine learning (ML) pipeline to identify star clusters in...
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10/06/2020
Shot in the Dark: Few-Shot Learning with No Base-Class Labels
Few-shot learning aims to learn classifiers for new objects from a small...
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08/03/2020
PhraseCut: Language-based Image Segmentation in the Wild
We consider the problem of segmenting image regions given a natural lang...
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08/03/2020
Describing Textures using Natural Language
Textures in natural images can be characterized by color, shape, periodi...
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06/26/2020
Unsupervised Discovery of Object Landmarks via Contrastive Learning
Given a collection of images, humans are able to discover landmarks of t...
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05/02/2020
Exploring and Predicting Transferability across NLP Tasks
Recent advances in NLP demonstrate the effectiveness of training large-s...
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04/24/2020
Detecting and Tracking Communal Bird Roosts in Weather Radar Data
The US weather radar archive holds detailed information about biological...
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04/08/2020
Deep Manifold Prior
We present a prior for manifold structured data, such as surfaces of 3D ...
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04/06/2020
Learning Generative Models of Shape Handles
We present a generative model to synthesize 3D shapes as sets of handles...
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03/30/2020
Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions
The problems of shape classification and part segmentation from 3D point...
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03/26/2020
ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds
We propose a novel, end-to-end trainable, deep network called ParSeNet t...
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12/22/2019
Neural Shape Parsers for Constructive Solid Geometry
Constructive Solid Geometry (CSG) is a geometric modeling technique that...
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12/18/2019
The Spectral Bias of the Deep Image Prior
The "deep image prior" proposed by Ulyanov et al. is an intriguing prope...
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10/08/2019
When Does Self-supervision Improve Few-shot Learning?
We present a technique to improve the generalization of deep representat...
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10/03/2019
Learning Point Embeddings from Shape Repositories for Few-Shot Segmentation
User generated 3D shapes in online repositories contain rich information...
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07/02/2019
Visualizing and Describing Fine-grained Categories as Textures
We analyze how categories from recent FGVC challenges can be described b...
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06/17/2019
Boosting Supervision with Self-Supervision for Few-shot Learning
We present a technique to improve the transferability of deep representa...
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06/11/2019
Inferring 3D Shapes from Image Collections using Adversarial Networks
We investigate the problem of learning a probabilistic distribution over...
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04/16/2019
Active Adversarial Domain Adaptation
We propose an active learning approach for transferring representations ...
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04/16/2019
A Bayesian Perspective on the Deep Image Prior
The deep image prior was recently introduced as a prior for natural imag...
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04/07/2019
Meta-Learning with Differentiable Convex Optimization
Many meta-learning approaches for few-shot learning rely on simple base ...
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02/10/2019
Task2Vec: Task Embedding for Meta-Learning
We introduce a method to provide vectorial representations of visual cla...
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09/07/2018
A Deeper Look at 3D Shape Classifiers
We investigate the role of representations and architectures for classif...
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08/22/2018
Second-order Democratic Aggregation
Aggregated second-order features extracted from deep convolutional netwo...
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07/10/2018
Multiresolution Tree Networks for 3D Point Cloud Processing
We present multiresolution tree-structured networks to process point clo...
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05/24/2018
VisemeNet: Audio-Driven Animator-Centric Speech Animation
We present a novel deep-learning based approach to producing animator-ce...
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02/22/2018
SPLATNet: Sparse Lattice Networks for Point Cloud Processing
We present a network architecture for processing point clouds that direc...
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12/22/2017
CSGNet: Neural Shape Parser for Constructive Solid Geometry
We present a neural architecture that takes as input a 2D or 3D shape an...
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07/21/2017
Improved Bilinear Pooling with CNNs
Bilinear pooling of Convolutional Neural Network (CNN) features [22, 23]...
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07/20/2017
3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks
We propose a method for reconstructing 3D shapes from 2D sketches in the...
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07/19/2017
Shape Generation using Spatially Partitioned Point Clouds
We propose a method to generate 3D shapes using point clouds. Given a po...
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12/18/2016
3D Shape Induction from 2D Views of Multiple Objects
In this paper we investigate the problem of inducing a distribution over...
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12/08/2016