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01/03/2023
Correlation Loss: Enforcing Correlation between Classification and Localization
Object detectors are conventionally trained by a weighted sum of classif...
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09/15/2022
AssembleRL: Learning to Assemble Furniture from Their Point Clouds
The rise of simulation environments has enabled learning-based approache...
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09/06/2022
Segment Augmentation and Differentiable Ranking for Logo Retrieval
Logo retrieval is a challenging problem since the definition of similari...
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04/13/2022
Does depth estimation help object detection?
Ground-truth depth, when combined with color data, helps improve object ...
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10/19/2021
Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation
This paper presents Mask-aware Intersection-over-Union (maIoU) for assig...
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07/24/2021
Rank Sort Loss for Object Detection and Instance Segmentation
We propose Rank Sort (RS) Loss, as a ranking-based loss function to ...
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11/21/2020
One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks
Despite being widely used as a performance measure for visual detection ...
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11/17/2020
Spatio-Temporal Analysis of Facial Actions using Lifecycle-Aware Capsule Networks
Most state-of-the-art approaches for Facial Action Unit (AU) detection r...
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11/13/2020
Transformer-Encoder Detector Module: Using Context to Improve Robustness to Adversarial Attacks on Object Detection
Deep neural network approaches have demonstrated high performance in obj...
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09/28/2020
A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
We propose average Localization-Recall-Precision (aLRP), a unified, boun...
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08/03/2020
Late Temporal Modeling in 3D CNN Architectures with BERT for Action Recognition
In this work, we combine 3D convolution with late temporal modeling for ...
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07/24/2020
Mind Your Manners! A Dataset and A Continual Learning Approach for Assessing Social Appropriateness of Robot Actions
To date, endowing robots with an ability to assess social appropriatenes...
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07/20/2020
Investigating Bias and Fairness in Facial Expression Recognition
Recognition of expressions of emotions and affect from facial images is ...
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10/25/2019
ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild
Robots collaborating with humans in realistic environments will need to ...
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09/21/2019
Generating Positive Bounding Boxes for Balanced Training of Object Detectors
Two-stage deep object detectors generate a set of regions-of-interest (R...
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08/31/2019
Imbalance Problems in Object Detection: A Review
In this paper, we present a comprehensive review of the imbalance proble...
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08/03/2019
Searching for Ambiguous Objects in Videos using Relational Referring Expressions
Humans frequently use referring (identifying) expressions to refer to ob...
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04/15/2019
Learning to Generate Unambiguous Spatial Referring Expressions for Real-World Environments
Referring to objects in a natural and unambiguous manner is crucial for ...
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07/04/2018
Localization Recall Precision (LRP): A New Performance Metric for Object Detection
Average precision (AP), the area under the recall-precision (RP) curve, ...
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07/02/2018
COSMO: Contextualized Scene Modeling with Boltzmann Machines
Scene modeling is very crucial for robots that need to perceive, reason ...
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10/16/2017
What is (missing or wrong) in the scene? A Hybrid Deep Boltzmann Machine For Contextualized Scene Modeling
Scene models allow robots to reason about what is in the scene, what els...
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10/13/2017
A Learning Based Approach to Incremental Context Modeling in Robots
There have been several attempts at modeling context in robots. However,...
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10/13/2017
A Deep Incremental Boltzmann Machine for Modeling Context in Robots
Context is an essential capability for robots that are to be as adaptive...
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06/18/2017
Using Deep Networks for Drone Detection
Drone detection is the problem of finding the smallest rectangle that en...
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01/20/2017
