b'Munawar Hayat'

research

∙ 05/14/2022

Transformer Scale Gate for Semantic Segmentation

Effectively encoding multi-scale contextual information is crucial for a...

Hengcan Shi, et al. ∙

research

∙ 04/13/2022

Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localization

Due to its high societal impact, deepfake detection is getting active at...

Zhixi Cai, et al. ∙

research

∙ 04/02/2022

Semantic-Aware Domain Generalized Segmentation

Deep models trained on source domain lack generalization when evaluated ...

Duo Peng, et al. ∙

research

∙ 03/31/2022

Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds

Point cloud scene flow estimation is of practical importance for dynamic...

Zhao Jin, et al. ∙

research

∙ 01/24/2022

Transformers in Medical Imaging: A Survey

Following unprecedented success on the natural language tasks, Transform...

Fahad Shamshad, et al. ∙

research

∙ 01/18/2022

ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues

Object proposal generation is an important and fundamental task in compu...

Hengcan Shi, et al. ∙

research

∙ 01/18/2022

Unpaired Referring Expression Grounding via Bidirectional Cross-Modal Matching

Referring expression grounding is an important and challenging task in c...

Hengcan Shi, et al. ∙

research

∙ 11/26/2021

A Volumetric Transformer for Accurate 3D Tumor Segmentation

This paper presents a Transformer architecture for volumetric medical im...

Himashi Peiris, et al. ∙

research

∙ 10/23/2021

MTGLS: Multi-Task Gaze Estimation with Limited Supervision

Robust gaze estimation is a challenging task, even for deep CNNs, due to...

Shreya Ghosh, et al. ∙

research

∙ 08/12/2021

Automatic Gaze Analysis: A Survey of DeepLearning based Approaches

Eye gaze analysis is an important research problem in the field of compu...

Shreya Ghosh, et al. ∙

research

∙ 03/26/2021

On Generating Transferable Targeted Perturbations

While the untargeted black-box transferability of adversarial perturbati...

Muzammal Naseer, et al. ∙

research

∙ 03/25/2021

Orthogonal Projection Loss

Deep neural networks have achieved remarkable performance on a range of ...

Kanchana Ranasinghe, et al. ∙

research

∙ 01/04/2021

Transformers in Vision: A Survey

Astounding results from transformer models on natural language tasks hav...

Salman Khan, et al. ∙

research

∙ 10/19/2020

Synthesizing the Unseen for Zero-shot Object Detection

The existing zero-shot detection approaches project visual features to t...

Nasir Hayat, et al. ∙

research

∙ 10/19/2020

Meta-learning the Learning Trends Shared Across Tasks

Meta-learning stands for 'learning to learn' such that generalization to...

Jathushan Rajasegaran, et al. ∙

research

∙ 09/25/2020

AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

This paper introduces the real image Super-Resolution (SR) challenge tha...

Pengxu Wei, et al. ∙

research

∙ 07/29/2020

Stylized Adversarial Defense

Deep Convolution Neural Networks (CNNs) can easily be fooled by subtle, ...

Muzammal Naseer, et al. ∙

research

∙ 06/17/2020

Self-supervised Knowledge Distillation for Few-shot Learning

Real-world contains an overwhelmingly large number of object classes, le...

Jathushan Rajasegaran, et al. ∙

research

∙ 06/08/2020

A Self-supervised Approach for Adversarial Robustness

Adversarial examples can cause catastrophic mistakes in Deep Neural Netw...

Muzammal Naseer, et al. ∙

research

∙ 03/25/2020

iTAML: An Incremental Task-Agnostic Meta-learning Approach

Humans can continuously learn new knowledge as their experience grows. I...

Jathushan Rajasegaran, et al. ∙

research

∙ 03/17/2020

CycleISP: Real Image Restoration via Improved Data Synthesis

The availability of large-scale datasets has helped unleash the true pot...

Syed Waqas Zamir, et al. ∙

research

∙ 03/15/2020

Learning Enriched Features for Real Image Restoration and Enhancement

With the goal of recovering high-quality image content from its degraded...

Syed Waqas Zamir, et al. ∙

research

∙ 02/21/2020

Towards Robust and Reproducible Active Learning Using Neural Networks

Active learning (AL) is a promising ML paradigm that has the potential t...

Prateek Munjal, et al. ∙

research

∙ 06/09/2019

Unsupervised Primitive Discovery for Improved 3D Generative Modeling

3D shape generation is a challenging problem due to the high-dimensional...

Salman H. Khan, et al. ∙

research

∙ 06/03/2019

Random Path Selection for Incremental Learning

Incremental life-long learning is a main challenge towards the long-stan...

Jathushan Rajasegaran, et al. ∙

research

∙ 04/08/2019

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...

Bilal Taha, et al. ∙

research

∙ 04/01/2019

Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

Deep neural networks are vulnerable to adversarial attacks, which can fo...

Aamir Mustafa, et al. ∙

research

∙ 01/23/2019

Max-margin Class Imbalanced Learning with Gaussian Affinity

Real-world object classes appear in imbalanced ratios. This poses a sign...

Munawar Hayat, et al. ∙

research

∙ 01/22/2019

Striking the Right Balance with Uncertainty

Learning unbiased models on imbalanced datasets is a significant challen...

Salman Khan, et al. ∙

research

∙ 01/07/2019

Image Super-Resolution as a Defense Against Adversarial Attacks

Convolutional Neural Networks have achieved significant success across m...

Aamir Mustafa, et al. ∙

research

∙ 04/27/2018

Adversarial Training of Variational Auto-encoders for High Fidelity Image Generation

Variational auto-encoders (VAEs) provide an attractive solution to image...

Salman H. Khan, et al. ∙

research

∙ 11/23/2017

Regularization of Deep Neural Networks with Spectral Dropout

The big breakthrough on the ImageNet challenge in 2012 was partially due...

Salman Khan, et al. ∙

research

∙ 06/18/2015

A Spatial Layout and Scale Invariant Feature Representation for Indoor Scene Classification

Unlike standard object classification, where the image to be classified ...

Munawar Hayat, et al. ∙

research

∙ 06/17/2015

A Discriminative Representation of Convolutional Features for Indoor Scene Recognition

Indoor scene recognition is a multi-faceted and challenging problem due ...

Salman H. Khan, et al. ∙

Munawar Hayat

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