b'Salman Khan'

Towards Open World Object Detection

Humans have a natural instinct to identify unknown object instances in t...
03/03/2021 ∙ by K J Joseph, et al. ∙ 8 ∙ share

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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...
03/01/2021 ∙ by Mamshad Nayeem Rizve, et al. ∙ 0 ∙ share

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ROAD: The ROad event Awareness Dataset for Autonomous Driving

Humans approach driving in a holistic fashion which entails, in particul...
02/23/2021 ∙ by Gurkirt Singh, et al. ∙ 0 ∙ share

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Robust normalizing flows using Bernstein-type polynomials

Normalizing flows (NFs) are a class of generative models that allows exa...
02/06/2021 ∙ by Sameera Ramasinghe, et al. ∙ 0 ∙ share

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Generative Multi-Label Zero-Shot Learning

Multi-label zero-shot learning strives to classify images into multiple ...
01/27/2021 ∙ by Akshita Gupta, et al. ∙ 10 ∙ share

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Transformers in Vision: A Survey

Astounding results from transformer models on natural language tasks hav...
01/04/2021 ∙ by Salman Khan, et al. ∙ 0 ∙ share

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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...
11/25/2020 ∙ by Sameera Ramasinghe, et al. ∙ 0 ∙ share

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Synthesizing the Unseen for Zero-shot Object Detection

The existing zero-shot detection approaches project visual features to t...
10/19/2020 ∙ by Nasir Hayat, et al. ∙ 0 ∙ share

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Meta-learning the Learning Trends Shared Across Tasks

Meta-learning stands for 'learning to learn' such that generalization to...
10/19/2020 ∙ by Jathushan Rajasegaran, et al. ∙ 0 ∙ share

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Conditional Generative Modeling via Learning the Latent Space

Although deep learning has achieved appealing results on several machine...
10/07/2020 ∙ by Sameera Ramasinghe, et al. ∙ 12 ∙ share

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Attention Guided Semantic Relationship Parsing for Visual Question Answering

Humans explain inter-object relationships with semantic labels that demo...
10/05/2020 ∙ by Moshiur Farazi, et al. ∙ 5 ∙ share

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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...
09/28/2020 ∙ by Taimur Hassan, et al. ∙ 1 ∙ share

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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...
09/25/2020 ∙ by Pengxu Wei, et al. ∙ 7 ∙ share

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Stylized Adversarial Defense

Deep Convolution Neural Networks (CNNs) can easily be fooled by subtle, ...
07/29/2020 ∙ by Muzammal Naseer, et al. ∙ 8 ∙ share

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Self-supervised Knowledge Distillation for Few-shot Learning

Real-world contains an overwhelmingly large number of object classes, le...
06/17/2020 ∙ by Jathushan Rajasegaran, et al. ∙ 77 ∙ share

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A Self-supervised Approach for Adversarial Robustness

Adversarial examples can cause catastrophic mistakes in Deep Neural Netw...
06/08/2020 ∙ by Muzammal Naseer, et al. ∙ 15 ∙ share

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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...
04/14/2020 ∙ by Taimur Hassan, et al. ∙ 2 ∙ share

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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...
03/30/2020 ∙ by Yaxing Wang, et al. ∙ 5 ∙ share

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iTAML: An Incremental Task-Agnostic Meta-learning Approach

Humans can continuously learn new knowledge as their experience grows. I...
03/25/2020 ∙ by Jathushan Rajasegaran, et al. ∙ 4 ∙ share

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CycleISP: Real Image Restoration via Improved Data Synthesis

The availability of large-scale datasets has helped unleash the true pot...
03/17/2020 ∙ by Syed Waqas Zamir, et al. ∙ 14 ∙ share

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Incremental Object Detection via Meta-Learning

In a real-world setting, object instances from new classes may be contin...
03/17/2020 ∙ by K J Joseph, et al. ∙ 11 ∙ share

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Any-Shot Object Detection

Previous work on novel object detection considers zero or few-shot setti...
03/16/2020 ∙ by Shafin Rahman, et al. ∙ 43 ∙ share

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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...
03/15/2020 ∙ by Syed Waqas Zamir, et al. ∙ 11 ∙ share

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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...
12/14/2019 ∙ by Guolei Sun, et al. ∙ 37 ∙ share

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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...
12/13/2019 ∙ by Hisham Cholakkal, et al. ∙ 9 ∙ share

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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...
12/04/2019 ∙ by Sameera Ramasinghe, et al. ∙ 19 ∙ share

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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...
11/30/2019 ∙ by Sameera Ramasinghe, et al. ∙ 0 ∙ share

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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...
09/11/2019 ∙ by Muhammad Haris Khan, et al. ∙ 7 ∙ share

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Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes

Existing networks directly learn feature representations on 3D point clo...
08/24/2019 ∙ by Sameera Ramasinghe, et al. ∙ 0 ∙ share

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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...
06/20/2019 ∙ by Qiuxia Lai, et al. ∙ 18 ∙ share

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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...
06/04/2019 ∙ by Guodong Ding, et al. ∙ 3 ∙ share

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Random Path Selection for Incremental Learning

Incremental life-long learning is a main challenge towards the long-stan...
06/03/2019 ∙ by Jathushan Rajasegaran, et al. ∙ 0 ∙ share

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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...
05/30/2019 ∙ by Syed Waqas Zamir, et al. ∙ 0 ∙ share

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A Deep Journey into Super-resolution: A survey

Deep convolutional networks based super-resolution is a fast-growing fie...
04/16/2019 ∙ by Saeed Anwar, et al. ∙ 28 ∙ share

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Learning Digital Camera Pipeline for Extreme Low-Light Imaging

In low-light conditions, a conventional camera imaging pipeline produces...
04/11/2019 ∙ by Syed Waqas Zamir, et al. ∙ 0 ∙ share

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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...
04/01/2019 ∙ by Aamir Mustafa, et al. ∙ 0 ∙ share

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Max-margin Class Imbalanced Learning with Gaussian Affinity

Real-world object classes appear in imbalanced ratios. This poses a sign...
01/23/2019 ∙ by Munawar Hayat, et al. ∙ 0 ∙ share

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Striking the Right Balance with Uncertainty

Learning unbiased models on imbalanced datasets is a significant challen...
01/22/2019 ∙ by Salman Khan, et al. ∙ 0 ∙ share

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Volumetric Convolution: Automatic Representation Learning in Unit Ball

Convolution is an efficient technique to obtain abstract feature represe...
01/03/2019 ∙ by Sameera Ramasinghe, et al. ∙ 0 ∙ share

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Polarity Loss for Zero-shot Object Detection

Zero-shot object detection is an emerging research topic that aims to re...
11/22/2018 ∙ by Shafin Rahman, et al. ∙ 0 ∙ share

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A Context-aware Capsule Network for Multi-label Classification

Recently proposed Capsule Network is a brain inspired architecture that ...
10/15/2018 ∙ by Sameera Ramasinghe, et al. ∙ 0 ∙ share

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Visual Affordance and Function Understanding: A Survey

Nowadays, robots are dominating the manufacturing, entertainment and hea...
07/18/2018 ∙ by Mohammed Hassanin, et al. ∙ 0 ∙ share

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Local Gradients Smoothing: Defense against localized adversarial attacks

Deep neural networks (DNNs) have shown vulnerability to adversarial atta...
07/03/2018 ∙ by Muzammal Naseer, et al. ∙ 8 ∙ share

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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...
05/16/2018 ∙ by Guodong Ding, et al. ∙ 0 ∙ share

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Reciprocal Attention Fusion for Visual Question Answering

Existing attention mechanisms either attend to local image grid or objec...
05/11/2018 ∙ by Moshiur R Farazi, et al. ∙ 0 ∙ share

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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...
03/16/2018 ∙ by Shafin Rahman, et al. ∙ 0 ∙ share

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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...
03/16/2018 ∙ by Shafin Rahman, et al. ∙ 0 ∙ share

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Regularization of Deep Neural Networks with Spectral Dropout

The big breakthrough on the ImageNet challenge in 2012 was partially due...
11/23/2017 ∙ by Salman Khan, et al. ∙ 0 ∙ share

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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...
11/20/2017 ∙ by Guodong Ding, et al. ∙ 0 ∙ share

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Salman Khan

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