research
∙
08/15/2023
Multimodal Dataset Distillation for Image-Text Retrieval
Dataset distillation methods offer the promise of reducing a large-scale...
share
research
∙
06/07/2023
ICON^2: Reliably Benchmarking Predictive Inequity in Object Detection
As computer vision systems are being increasingly deployed at scale in h...
research
∙
06/07/2023
Art and the science of generative AI: A deeper dive
A new class of tools, colloquially called generative AI, can produce hig...
research
∙
05/15/2023
Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application
Trust is an important factor in people's interactions with AI systems. H...
research
∙
03/27/2023
UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs
Concept-based explanations for convolutional neural networks (CNNs) aim ...
research
∙
03/10/2023
Overcoming Bias in Pretrained Models by Manipulating the Finetuning Dataset
Transfer learning is beneficial by allowing the expressive features of m...
research
∙
02/16/2023
Boundary Guided Mixing Trajectory for Semantic Control with Diffusion Models
Applying powerful generative denoising diffusion models (DDMs) for downs...
research
∙
01/05/2023
Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset
Current dataset collection methods typically scrape large amounts of dat...
research
∙
10/02/2022
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction
Despite the proliferation of explainable AI (XAI) methods, little is und...
research
∙
07/27/2022
SiRi: A Simple Selective Retraining Mechanism for Transformer-based Visual Grounding
In this paper, we investigate how to achieve better visual grounding wit...
research
∙
07/20/2022
Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability
Concept-based interpretability methods aim to explain deep neural networ...
research
∙
07/07/2022
Predicting Word Learning in Children from the Performance of Computer Vision Systems
For human children as well as machine learning systems, a key challenge ...
research
∙
06/18/2022
Gender Artifacts in Visual Datasets
Gender biases are known to exist within large-scale visual datasets and ...
research
∙
06/15/2022
ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features
Deep learning models have achieved remarkable success in different areas...
research
∙
06/06/2022
Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks
We propose an algorithm that compresses the critical information of a la...
research
∙
05/10/2022
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Research in machine learning fairness has historically considered a sing...
research
∙
03/15/2022
CARETS: A Consistency And Robustness Evaluative Test Suite for VQA
We introduce CARETS, a systematic test suite to measure consistency and ...
research
∙
01/10/2022
Multi-query Video Retrieval
Retrieving target videos based on text descriptions is a task of great p...
research
∙
12/06/2021
HIVE: Evaluating the Human Interpretability of Visual Explanations
As machine learning is increasingly applied to high-impact, high-risk do...
research
∙
06/16/2021
Understanding and Evaluating Racial Biases in Image Captioning
Image captioning is an important task for benchmarking visual reasoning ...
research
∙
04/28/2021
[Re] Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias
Singh et al. (2020) point out the dangers of contextual bias in visual r...
research
∙
03/10/2021
A Study of Face Obfuscation in ImageNet
Face obfuscation (blurring, mosaicing, etc.) has been shown to be effect...
research
∙
02/24/2021
Directional Bias Amplification
Mitigating bias in machine learning systems requires refining our unders...
research
∙
12/02/2020
Fair Attribute Classification through Latent Space De-biasing
Fairness in visual recognition is becoming a prominent and critical topi...
research
∙
11/27/2020
Point and Ask: Incorporating Pointing into Visual Question Answering
Visual Question Answering (VQA) has become one of the key benchmarks of ...
research
∙
09/08/2020
Towards Unique and Informative Captioning of Images
Despite considerable progress, state of the art image captioning models ...
research
∙
07/11/2020
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
The ability to perform effective planning is crucial for building an ins...
research
∙
04/16/2020
ViBE: A Tool for Measuring and Mitigating Bias in Image Datasets
Machine learning models are known to perpetuate the biases present in th...
research
∙
03/31/2020
Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation
In the Vision-and-Language Navigation (VLN) task, an agent with egocentr...
research
∙
12/16/2019
Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy
Computer vision technology is being used by many but remains representat...
research
∙
12/04/2019
Compositional Temporal Visual Grounding of Natural Language Event Descriptions
Temporal grounding entails establishing a correspondence between natural...
research
∙
11/26/2019
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation
Computer vision models learn to perform a task by capturing relevant sta...
research
∙
08/19/2019
Human uncertainty makes classification more robust
The classification performance of deep neural networks has begun to asym...
research
∙
08/07/2019
SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition
Understanding the spatial relations between objects in images is a surpr...
research
∙
04/18/2019
CornerNet-Lite: Efficient Keypoint Based Object Detection
Keypoint-based methods are a relatively new paradigm in object detection...
research
∙
08/09/2017
What Actions are Needed for Understanding Human Actions in Videos?
What is the right way to reason about human activities? What directions ...
research
∙
06/09/2017
Learning to Learn from Noisy Web Videos
Understanding the simultaneously very diverse and intricately fine-grain...
research
∙
04/12/2017
What's in a Question: Using Visual Questions as a Form of Supervision
Collecting fully annotated image datasets is challenging and expensive. ...
research
∙
04/12/2017
Predictive-Corrective Networks for Action Detection
While deep feature learning has revolutionized techniques for static-ima...
research
∙
11/07/2016
Crowdsourcing in Computer Vision
Computer vision systems require large amounts of manually annotated data...
research
∙
07/25/2016
Much Ado About Time: Exhaustive Annotation of Temporal Data
Large-scale annotated datasets allow AI systems to learn from and build ...
research
∙
11/22/2015
End-to-end Learning of Action Detection from Frame Glimpses in Videos
In this work we introduce a fully end-to-end approach for action detecti...
research
∙
07/21/2015
Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos
Every moment counts in action recognition. A comprehensive understanding...
research
∙
06/06/2015
What's the Point: Semantic Segmentation with Point Supervision
The semantic image segmentation task presents a trade-off between test t...
research
∙
03/02/2015
Joint calibration of Ensemble of Exemplar SVMs
We present a method for calibrating the Ensemble of Exemplar SVMs model....
research
∙
09/01/2014
