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08/29/2023
Unveiling Camouflage: A Learnable Fourier-based Augmentation for Camouflaged Object Detection and Instance Segmentation
Camouflaged object detection (COD) and camouflaged instance segmentation...
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08/29/2023
Few-Shot Object Detection via Synthetic Features with Optimal Transport
Few-shot object detection aims to simultaneously localize and classify t...
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06/07/2023
Optimal Transport Model Distributional Robustness
Distributional robustness is a promising framework for training deep lea...
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05/31/2023
Noisy-label Learning with Sample Selection based on Noise Rate Estimate
Noisy-labels are challenging for deep learning due to the high capacity ...
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04/15/2023
Instance-level Few-shot Learning with Class Hierarchy Mining
Few-shot learning is proposed to tackle the problem of scarce training d...
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04/15/2023
Few-shot Camouflaged Animal Detection and Segmentation
Camouflaged object detection and segmentation is a new and challenging r...
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03/31/2023
Robotic Perception of Transparent Objects: A Review
Transparent object perception is a rapidly developing research problem i...
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03/20/2023
PASS: Peer-Agreement based Sample Selection for training with Noisy Labels
Noisy labels present a significant challenge in deep learning because mo...
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03/09/2023
MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation
Few-shot instance segmentation extends the few-shot learning paradigm to...
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02/06/2023
Flat Seeking Bayesian Neural Networks
Bayesian Neural Networks (BNNs) offer a probabilistic interpretation for...
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01/04/2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach
Learning from noisy labels plays an important role in the deep learning ...
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01/04/2023
Task Weighting in Meta-learning with Trajectory Optimisation
Developing meta-learning algorithms that are un-biased toward a subset o...
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10/14/2022
Vision Transformer Visualization: What Neurons Tell and How Neurons Behave?
Recently vision transformers (ViT) have been applied successfully for va...
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09/02/2022
Instance-Dependent Noisy Label Learning via Graphical Modelling
Noisy labels are unavoidable yet troublesome in the ecosystem of deep le...
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08/20/2022
Where Shall I Touch? Vision-Guided Tactile Poking for Transparent Object Grasping
Picking up transparent objects is still a challenging task for robots. T...
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07/11/2022
A4T: Hierarchical Affordance Detection for Transparent Objects Depth Reconstruction and Manipulation
Transparent objects are widely used in our daily lives and therefore rob...
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11/01/2021
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification
The shipping industry is an important component of the global trade and ...
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06/09/2021
Probabilistic task modelling for meta-learning
We propose probabilistic task modelling – a generative probabilistic mod...
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03/31/2021
Camouflaged Instance Segmentation: Dataset and Benchmark Suite
This paper pushes the envelope on camouflaged regions to decompose them ...
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01/27/2021
Similarity of Classification Tasks
Recent advances in meta-learning has led to remarkable performances on s...
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09/23/2020
Multiple interaction learning with question-type prior knowledge for constraining answer search space in visual question answering
Different approaches have been proposed to Visual Question Answering (VQ...
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09/09/2020
Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding
Unsupervised Deep Distance Metric Learning (UDML) aims to learn sample s...
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07/25/2020
MirrorNet: Bio-Inspired Adversarial Attack for Camouflaged Object Segmentation
Camouflaged objects are generally difficult to be detected in their natu...
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05/15/2020
Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking
The field of Human Activity Recognition (HAR) focuses on obtaining and a...
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03/05/2020
PAC-Bayesian Meta-learning with Implicit Prior
We introduce a new and rigorously-formulated PAC-Bayes few-shot meta-lea...
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09/26/2019
Compact Trilinear Interaction for Visual Question Answering
In Visual Question Answering (VQA), answers have a great correlation wit...
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09/26/2019
Overcoming Data Limitation in Medical Visual Question Answering
Traditional approaches for Visual Question Answering (VQA) require large...
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08/01/2019
Scalable Place Recognition Under Appearance Change for Autonomous Driving
A major challenge in place recognition for autonomous driving is to be r...
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07/27/2019
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
We introduce a new, rigorously-formulated Bayesian meta-learning algorit...
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04/26/2019
Bayesian Generative Active Deep Learning
Deep learning models have demonstrated outstanding performance in severa...
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04/24/2019
Simultaneous Feature Aggregating and Hashing for Compact Binary Code Learning
Representing images by compact hash codes is an attractive approach for ...
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04/18/2019
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
We propose a method that substantially improves the efficiency of deep d...
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04/06/2019
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences
This paper presents a novel randomized algorithm for robust point cloud ...
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03/23/2019
V2CNet: A Deep Learning Framework to Translate Videos to Commands for Robotic Manipulation
We propose V2CNet, a new deep learning framework to automatically transl...
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02/05/2019
SASSE: Scalable and Adaptable 6-DOF Pose Estimation
Visual localization has become a key enabling component of many place re...
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01/12/2019
Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes
As the post-processing step for object detection, non-maximum suppressio...
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11/20/2018
Practical Visual Localization for Autonomous Driving: Why Not Filter?
A major focus of current research on place recognition is visual localiz...
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10/24/2018
A Binary Optimization Approach for Constrained K-Means Clustering
K-Means clustering still plays an important role in many computer vision...
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07/03/2018
MediaEval 2018: Predicting Media Memorability Task
In this paper, we present the Predicting Media Memorability task, which ...
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06/16/2018
G2D: from GTA to Data
This document describes G2D, a software that enables capturing videos fr...
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06/04/2018
Bayesian Semantic Instance Segmentation in Open Set World
This paper addresses the instance segmentation task in the open-set cond...
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03/16/2018
Object Captioning and Retrieval with Natural Language
We address the problem of jointly learning vision and language to unders...
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02/28/2018
Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image
Detecting objects and their 6D poses from only RGB images is an importan...
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02/21/2018
Binary Constrained Deep Hashing Network for Image Retrieval without Human Intervention
Learning compact binary codes for image retrieval problem using deep neu...
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02/19/2018
Simultaneous Compression and Quantization: A Joint Approach for Efficient Unsupervised Hashing
The two most important requirements for unsupervised data-dependent hash...
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02/10/2018
On-device Scalable Image-based Localization
We present the scalable design of an entire on-device system for large-s...
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02/07/2018
From Selective Deep Convolutional Features to Compact Binary Representations for Image Retrieval
Convolutional Neural Network (CNN) is a very powerful approach to extrac...
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12/08/2017
Compact Hash Code Learning with Binary Deep Neural Network
In this work, we firstly propose deep network models and learning algori...
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11/24/2017
Supervised Hashing with End-to-End Binary Deep Neural Network
Image hashing is a popular technique applied to large scale content-base...
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09/21/2017
