research
∙
08/10/2023
Benchmarking Algorithmic Bias in Face Recognition: An Experimental Approach Using Synthetic Faces and Human Evaluation
We propose an experimental method for measuring bias in face recognition...
share
research
∙
06/05/2023
Spatial Implicit Neural Representations for Global-Scale Species Mapping
Estimating the geographical range of a species from sparse observations ...
research
∙
06/01/2023
Confidence Intervals for Error Rates in Matching Tasks: Critical Review and Recommendations
Matching algorithms are commonly used to predict matches between items i...
research
∙
05/24/2023
Understanding Label Bias in Single Positive Multi-Label Learning
Annotating data for multi-label classification is prohibitively expensiv...
research
∙
12/14/2022
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos
Quantifying motion in 3D is important for studying the behavior of human...
research
∙
07/21/2022
The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior
Real-world behavior is often shaped by complex interactions between mult...
research
∙
07/20/2022
On Label Granularity and Object Localization
Weakly supervised object localization (WSOL) aims to learn representatio...
research
∙
07/20/2022
Visual Knowledge Tracing
Each year, thousands of people learn new visual categorization tasks – r...
research
∙
07/19/2022
The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting
We present the Caltech Fish Counting Dataset (CFC), a large-scale datase...
research
∙
02/11/2022
Towards Weakly-Supervised Text Spotting using a Multi-Task Transformer
Text spotting end-to-end methods have recently gained attention in the l...
research
∙
01/25/2022
Rayleigh EigenDirections (REDs): GAN latent space traversals for multidimensional features
We present a method for finding paths in a deep generative model's laten...
research
∙
12/09/2021
Self-Supervised Keypoint Discovery in Behavioral Videos
We propose a method for learning the posture and structure of agents fro...
research
∙
09/28/2021
Weakly Supervised Keypoint Discovery
In this paper, we propose a method for keypoint discovery from a 2D imag...
research
∙
07/03/2021
Species Distribution Modeling for Machine Learning Practitioners: A Review
Conservation science depends on an accurate understanding of what's happ...
research
∙
06/17/2021
Multi-Label Learning from Single Positive Labels
Predicting all applicable labels for a given image is known as multi-lab...
research
∙
04/06/2021
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions
Multi-agent behavior modeling aims to understand the interactions that o...
research
∙
01/29/2021
A linearized framework and a new benchmark for model selection for fine-tuning
Fine-tuning from a collection of models pre-trained on different domains...
research
∙
12/08/2020
A Number Sense as an Emergent Property of the Manipulating Brain
The ability to understand and manipulate numbers and quantities emerges ...
research
∙
11/27/2020
Task Programming: Learning Data Efficient Behavior Representations
Specialized domain knowledge is often necessary to accurately annotate t...
research
∙
07/13/2020
Towards causal benchmarking of bias in face analysis algorithms
Measuring algorithmic bias is crucial both to assess algorithmic fairnes...
research
∙
03/03/2020
Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications
Trained on large datasets, deep learning (DL) can accurately classify vi...
research
∙
02/05/2020
Geocoding of trees from street addresses and street-level images
We introduce an approach for updating older tree inventories with geogra...
research
∙
12/31/2019
HMM-guided frame querying for bandwidth-constrained video search
We design an agent to search for frames of interest in video stored on a...
research
∙
11/27/2019
PanDA: Panoptic Data Augmentation
The recently proposed panoptic segmentation task presents a significant ...
research
∙
10/07/2019
From Google Maps to a Fine-Grained Catalog of Street trees
Up-to-date catalogs of the urban tree population are important for munic...
research
∙
09/24/2019
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
We propose a novel loss function that dynamically rescales the cross ent...
research
∙
07/15/2019
The iWildCam 2019 Challenge Dataset
Camera Traps (or Wild Cams) enable the automatic collection of large qua...
research
∙
06/12/2019
Presence-Only Geographical Priors for Fine-Grained Image Classification
Appearance information alone is often not sufficient to accurately diffe...
research
∙
04/11/2019
The iWildCam 2018 Challenge Dataset
Camera traps are a valuable tool for studying biodiversity, but research...
research
∙
04/11/2019
Synthetic Examples Improve Generalization for Rare Classes
The ability to detect and classify rare occurrences in images has import...
research
∙
02/10/2019
Task2Vec: Task Embedding for Meta-Learning
We introduce a method to provide vectorial representations of visual cla...
research
∙
07/13/2018
Recognition in Terra Incognita
It is desirable for detection and classification algorithms to generaliz...
research
∙
05/21/2018
Teaching Multiple Concepts to Forgetful Learners
How can we help a forgetful learner learn multiple concepts within a lim...
research
∙
05/17/2018
It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data
We address the problem of 3D human pose estimation from 2D input images ...
research
∙
04/08/2018
Fast Conditional Independence Test for Vector Variables with Large Sample Sizes
We present and evaluate the Fast (conditional) Independence Test (FIT) -...
research
∙
02/20/2018
Teaching Categories to Human Learners with Visual Explanations
We study the problem of computer-assisted teaching with explanations. Co...
research
∙
02/14/2018
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners
In real-world applications of education and human teaching, an effective...
research
∙
09/22/2017
Context Embedding Networks
Low dimensional embeddings that capture the main variations of interest ...
research
∙
09/05/2017
The Devil is in the Tails: Fine-grained Classification in the Wild
The world is long-tailed. What does this mean for computer vision and vi...
research
∙
07/20/2017
The iNaturalist Challenge 2017 Dataset
Existing image classification datasets used in computer vision tend to h...
research
∙
07/17/2017
Benchmarking and Error Diagnosis in Multi-Instance Pose Estimation
We propose a new method to analyze the impact of errors in algorithms fo...
research
∙
03/17/2017
Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
We propose and systematically evaluate three strategies for training dyn...
research
∙
11/04/2016
Estimating Causal Direction and Confounding of Two Discrete Variables
We propose a method to classify the causal relationship between two disc...
research
∙
11/01/2016
Learning recurrent representations for hierarchical behavior modeling
We propose a framework for detecting action patterns from motion sequenc...
research
∙
10/03/2016
Seeing into Darkness: Scotopic Visual Recognition
Images are formed by counting how many photons traveling from a given se...
research
∙
07/12/2016
Improved Multi-Class Cost-Sensitive Boosting via Estimation of the Minimum-Risk Class
We present a simple unified framework for multi-class cost-sensitive boo...
research
∙
05/30/2016
Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data
We show that the climate phenomena of El Nino and La Nina arise naturall...
research
∙
05/20/2016
Fine-Grained Classification of Pedestrians in Video: Benchmark and State of the Art
A video dataset that is designed to study fine-grained categorisation of...
research
∙
12/25/2015
Multi-Level Cause-Effect Systems
We present a domain-general account of causation that applies to setting...
research
∙
06/07/2015