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Towards Open World Object Detection
Humans have a natural instinct to identify unknown object instances in t...
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Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
In many real-world problems, collecting a large number of labeled sample...
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ROAD: The ROad event Awareness Dataset for Autonomous Driving
Humans approach driving in a holistic fashion which entails, in particul...
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Robust normalizing flows using Bernstein-type polynomials
Normalizing flows (NFs) are a class of generative models that allows exa...
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Generative Multi-Label Zero-Shot Learning
Multi-label zero-shot learning strives to classify images into multiple ...
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Transformers in Vision: A Survey
Astounding results from transformer models on natural language tasks hav...
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How to train your conditional GAN: An approach using geometrically structured latent manifolds
Conditional generative modeling typically requires capturing one-to-many...
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Synthesizing the Unseen for Zero-shot Object Detection
The existing zero-shot detection approaches project visual features to t...
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Meta-learning the Learning Trends Shared Across Tasks
Meta-learning stands for 'learning to learn' such that generalization to...
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Conditional Generative Modeling via Learning the Latent Space
Although deep learning has achieved appealing results on several machine...
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Attention Guided Semantic Relationship Parsing for Visual Question Answering
Humans explain inter-object relationships with semantic labels that demo...
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Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion
Detecting baggage threats is one of the most difficult tasks, even for e...
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AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
This paper introduces the real image Super-Resolution (SR) challenge tha...
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Stylized Adversarial Defense
Deep Convolution Neural Networks (CNNs) can easily be fooled by subtle, ...
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Self-supervised Knowledge Distillation for Few-shot Learning
Real-world contains an overwhelmingly large number of object classes, le...
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A Self-supervised Approach for Adversarial Robustness
Adversarial examples can cause catastrophic mistakes in Deep Neural Netw...
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Cascaded Structure Tensor Framework for Robust Identification of Heavily Occluded Baggage Items from X-ray Scans
In the last two decades, baggage scanning has globally become one of the...
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Semi-supervised Learning for Few-shot Image-to-Image Translation
In the last few years, unpaired image-to-image translation has witnessed...
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iTAML: An Incremental Task-Agnostic Meta-learning Approach
Humans can continuously learn new knowledge as their experience grows. I...
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CycleISP: Real Image Restoration via Improved Data Synthesis
The availability of large-scale datasets has helped unleash the true pot...
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Incremental Object Detection via Meta-Learning
In a real-world setting, object instances from new classes may be contin...
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Any-Shot Object Detection
Previous work on novel object detection considers zero or few-shot setti...
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Learning Enriched Features for Real Image Restoration and Enhancement
With the goal of recovering high-quality image content from its degraded...
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Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes
The main requisite for fine-grained recognition task is to focus on subt...
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Towards Partial Supervision for Generic Object Counting in Natural Scenes
Generic object counting in natural scenes is a challenging computer visi...
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Spectral-GANs for High-Resolution 3D Point-cloud Generation
Point-clouds are a popular choice for vision and graphics tasks due to t...
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Representation Learning on Unit Ball with 3D Roto-Translational Equivariance
Convolution is an integral operation that defines how the shape of one f...
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AnimalWeb: A Large-Scale Hierarchical Dataset of Annotated Animal Faces
Being heavily reliant on animals, it is our ethical obligation to improv...
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Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes
Existing networks directly learn feature representations on 3D point clo...
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Human vs Machine Attention in Neural Networks: A Comparative Study
Recent years have witnessed a surge in the popularity of attention mecha...
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Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification
Person re-identification aims to establish the correct identity correspo...
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Random Path Selection for Incremental Learning
Incremental life-long learning is a main challenge towards the long-stan...
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iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
Existing Earth Vision datasets are either suitable for semantic segmenta...
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A Deep Journey into Super-resolution: A survey
Deep convolutional networks based super-resolution is a fast-growing fie...
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Learning Digital Camera Pipeline for Extreme Low-Light Imaging
In low-light conditions, a conventional camera imaging pipeline produces...
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Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks
Deep neural networks are vulnerable to adversarial attacks, which can fo...
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Max-margin Class Imbalanced Learning with Gaussian Affinity
Real-world object classes appear in imbalanced ratios. This poses a sign...
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Striking the Right Balance with Uncertainty
Learning unbiased models on imbalanced datasets is a significant challen...
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Volumetric Convolution: Automatic Representation Learning in Unit Ball
Convolution is an efficient technique to obtain abstract feature represe...
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Polarity Loss for Zero-shot Object Detection
Zero-shot object detection is an emerging research topic that aims to re...
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A Context-aware Capsule Network for Multi-label Classification
Recently proposed Capsule Network is a brain inspired architecture that ...
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Visual Affordance and Function Understanding: A Survey
Nowadays, robots are dominating the manufacturing, entertainment and hea...
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Local Gradients Smoothing: Defense against localized adversarial attacks
Deep neural networks (DNNs) have shown vulnerability to adversarial atta...
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Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification
Person re-identification aims to match a person's identity across multip...
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Reciprocal Attention Fusion for Visual Question Answering
Existing attention mechanisms either attend to local image grid or objec...
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Deep Multiple Instance Learning for Zero-shot Image Tagging
In-line with the success of deep learning on traditional recognition pro...
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Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts
Current Zero-Shot Learning (ZSL) approaches are restricted to recognitio...
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Regularization of Deep Neural Networks with Spectral Dropout
The big breakthrough on the ImageNet challenge in 2012 was partially due...
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Let Features Decide for Themselves: Feature Mask Network for Person Re-identification
Person re-identification aims at establishing the identity of a pedestri...
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