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Transformers in Vision: A Survey
Astounding results from transformer models on natural language tasks hav...
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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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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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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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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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Towards Robust and Reproducible Active Learning Using Neural Networks
Active learning (AL) is a promising ML paradigm that has the potential t...
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Unsupervised Primitive Discovery for Improved 3D Generative Modeling
3D shape generation is a challenging problem due to the high-dimensional...
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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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Learned 3D Shape Representations Using Fused Geometrically Augmented Images: Application to Facial Expression and Action Unit Detection
This paper proposes an approach to learn generic multi-modal mesh surfac...
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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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Image Super-Resolution as a Defense Against Adversarial Attacks
Convolutional Neural Networks have achieved significant success across m...
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Adversarial Training of Variational Auto-encoders for High Fidelity Image Generation
Variational auto-encoders (VAEs) provide an attractive solution to image...
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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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A Spatial Layout and Scale Invariant Feature Representation for Indoor Scene Classification
Unlike standard object classification, where the image to be classified ...
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A Discriminative Representation of Convolutional Features for Indoor Scene Recognition
Indoor scene recognition is a multi-faceted and challenging problem due ...
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