Search Results for author: Waqas Sultani

Found 19 papers, 3 papers with code

Mapping Temporary Slums from Satellite Imagery using a Semi-Supervised Approach

no code implementations9 Apr 2022 M. Fasi ur Rehman, Izza Ali, Waqas Sultani, Mohsen Ali

A small set of seed samples (32 in our case) are automatically discovered by analyzing the temporal changes, which are manually labeled to train a segmentation and representation learning module.

Representation Learning Semi-Supervised Semantic Segmentation

Visual and Object Geo-localization: A Comprehensive Survey

no code implementations30 Dec 2021 Daniel Wilson, Xiaohan Zhang, Waqas Sultani, Safwan Wshah

The concept of geo-localization refers to the process of determining where on earth some `entity' is located, typically using Global Positioning System (GPS) coordinates.

3D Reconstruction

Towards Low-Cost and Efficient Malaria Detection

no code implementations CVPR 2022 Waqas Sultani, Wajahat Nawaz, Syed Javed, Muhammad Sohail Danish, Asma Saadia, Mohsen Ali

We design a mechanism to transfer these annotations from the high-cost microscope at high magnification to the low-cost microscope, at multiple magnifications.

Domain Adaptation

Out of distribution detection for skin and malaria images

no code implementations2 Nov 2021 Muhammad Zaida, Shafaqat Ali, Mohsen Ali, Sarfaraz Hussein, Asma Saadia, Waqas Sultani

Deep neural networks have shown promising results in disease detection and classification using medical image data.

Metric Learning OOD Detection +1

Cross-Region Building Counting in Satellite Imagery using Counting Consistency

no code implementations26 Oct 2021 Muaaz Zakria, Hamza Rawal, Waqas Sultani, Mohsen Ali

We then exploit counting consistency constraints, within-image count consistency, and across-image count consistency, to decrease the domain shift.

Unsupervised Domain Adaptation

Estimation of BMI from Facial Images using Semantic Segmentation based Region-Aware Pooling

no code implementations10 Apr 2021 Nadeem Yousaf, Sarfaraz Hussein, Waqas Sultani

The recent works have either employed hand-crafted geometrical face features or face-level deep convolutional neural network features for face to BMI prediction.

Semantic Segmentation

Dogfight: Detecting Drones from Drones Videos

1 code implementation CVPR 2021 Muhammad Waseem Ashraf, Waqas Sultani, Mubarak Shah

The erratic movement of the source and target drones, small size, arbitrary shape, large intensity variations, and occlusion make this problem quite challenging.

Region Proposal

A Dataset and Benchmark for Malaria Life-Cycle Classification in Thin Blood Smear Images

no code implementations17 Feb 2021 Qazi Ammar Arshad, Mohsen Ali, Saeed-Ul Hassan, Chen Chen, Ayisha Imran, Ghulam Rasul, Waqas Sultani

Malaria microscopy, microscopic examination of stained blood slides to detect parasite Plasmodium, is considered to be a gold-standard for detecting life-threatening disease malaria.

General Classification

Fake Visual Content Detection Using Two-Stream Convolutional Neural Networks

no code implementations3 Jan 2021 Bilal Yousaf, Muhammad Usama, Waqas Sultani, Arif Mahmood, Junaid Qadir

The proposed detector has demonstrated significant performance improvement compared to the current state-of-the-art fake content detectors and fusing the frequency and spatial domain streams has also improved generalization of the detector.

Action recognition in real-world videos

no code implementations22 Apr 2020 Waqas Sultani, Qazi Ammar Arshad, Chen Chen

Temporal localization (i. e. indicating the start and end frames of the action in a video) is referred to as frame-level detection.

Action Recognition Temporal Localization

Video Anomaly Detection for Smart Surveillance

no code implementations1 Apr 2020 Sijie Zhu, Chen Chen, Waqas Sultani

Temporal localization (i. e. indicating the start and end frames of the anomaly event in a video) is referred to as frame-level detection.

Anomaly Detection Computer Vision +1

Human Action Recognition in Drone Videos using a Few Aerial Training Examples

no code implementations22 Oct 2019 Waqas Sultani, Mubarak Shah

However, using deep neural networks for automatic aerial action recognition is difficult due to the need for a large number of training aerial human action videos.

Action Classification Action Recognition

Deep Built-Structure Counting in Satellite Imagery Using Attention Based Re-Weighting

no code implementations1 Apr 2019 Anza Shakeel, Waqas Sultani, Mohsen Ali

In this paper, we attempt to address the challenging problem of counting built-structures in the satellite imagery.

Real-world Anomaly Detection in Surveillance Videos

7 code implementations CVPR 2018 Waqas Sultani, Chen Chen, Mubarak Shah

To avoid annotating the anomalous segments or clips in training videos, which is very time consuming, we propose to learn anomaly through the deep multiple instance ranking framework by leveraging weakly labeled training videos, i. e. the training labels (anomalous or normal) are at video-level instead of clip-level.

Activity Recognition Anomaly Detection In Surveillance Videos +2

Unsupervised Action Proposal Ranking through Proposal Recombination

no code implementations3 Apr 2017 Waqas Sultani, Dong Zhang, Mubarak Shah

Given the action proposals in a video, the goal of the proposed work is to generate a few better action proposals that are ranked properly.

Action Detection Action Recognition

What If We Do Not Have Multiple Videos of the Same Action? -- Video Action Localization Using Web Images

no code implementations CVPR 2016 Waqas Sultani, Mubarak Shah

%We reconstruct video action proposals from image action proposals while enforcing consistency across coefficient vectors of multiple frames by consensus regularization.

Optical Flow Estimation Spatio-Temporal Action Localization +1

Automatic Action Annotation in Weakly Labeled Videos

no code implementations26 May 2016 Waqas Sultani, Mubarak Shah

The output of our method is the most action representative proposals from each video.

Optical Flow Estimation

Human Action Recognition Across Datasets by Foreground-weighted Histogram Decomposition

no code implementations CVPR 2014 Waqas Sultani, Imran Saleemi

This paper attempts to address the problem of recognizing human actions while training and testing on distinct datasets, when test videos are neither labeled nor available during training.

Action Recognition

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