7 citations · 21 across the 14 of their papers we have counts for
15 papers
LoomSC: Scalable Deep Subspace Clustering with Projector Factorization and Exact Spectral Reduction
Nairouz Mrabah, Youssef Melki, Mohamed Bouguessa +3
Dense self-expression matrices and full-affinity spectral clustering limit the scalability of subspace clustering. We introduce the Latent Orthogonal Optimization Model for Subspac…
Seeing What Shouldn't Be There: Counterfactual GANs for Medical Image Attribution
Shakeeb Murtaza
Ascription of an image gives insights into the objects that influence the classification of the whole image or its pixels towards a specific category. These insights help radiologi…
InterPartAbility: Phrase-Region Grounding for Interpretable Text-to-Image Person Re-Identification
Shakeeb Murtaza, Aryan Shukla, Rajarshi Bhattacharya +2
Text-to-image person re-identification (TI-ReID) relies on natural-language text descriptions to retrieve top matching individuals from a gallery of reference images. While recent…
DART: Leveraging Distance for Test Time Adaptation in Person Re-Identification
Rajarshi Bhattacharya, Shakeeb Murtaza, Christian Desrosiers +3
Person re-identification (ReID) models are known to suffer from camera bias, where learned representations cluster according to camera viewpoints rather than identity, leading to s…
TeD-Loc: Text Distillation for Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Alexis Guichemerre +2
Weakly supervised object localization (WSOL) models can predict both the object class and the spatial regions corresponding to the object, without requiring explicit bounding-box a…
Leveraging Transformers for Weakly Supervised Object Localization in Unconstrained Videos
Shakeeb Murtaza, Marco Pedersoli, Aydin Sarraf +1
Weakly-Supervised Video Object Localization (WSVOL) involves localizing an object in videos using only video-level labels, also referred to as tags. State-of-the-art WSVOL methods…
SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-Resolution
Soufiane Belharbi, Mara KM Whitford, Phuong Hoang +3
Confocal fluorescence microscopy is one of the most accessible and widely used imaging techniques for the study of biological processes at the cellular and subcellular levels. Scan…
Source-Free Domain Adaptation of Weakly-Supervised Object Localization Models for Histology
Alexis Guichemerre, Soufiane Belharbi, Tsiry Mayet +4
Given the emergence of deep learning, digital pathology has gained popularity for cancer diagnosis based on histology images. Deep weakly supervised object localization (WSOL) mode…
A Realistic Protocol for Evaluation of Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Marco Pedersoli +1
Weakly Supervised Object Localization (WSOL) allows training deep learning models for classification and localization (LOC) using only global class-level labels. The absence of bou…
DiPS: Discriminative Pseudo-Label Sampling with Self-Supervised Transformers for Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Marco Pedersoli +2
Self-supervised vision transformers (SSTs) have shown great potential to yield rich localization maps that highlight different objects in an image. However, these maps remain class…
CoLo-CAM: Class Activation Mapping for Object Co-Localization in Weakly-Labeled Unconstrained Videos
Soufiane Belharbi, Shakeeb Murtaza, Marco Pedersoli +3
Leveraging spatiotemporal information in videos is critical for weakly supervised video object localization (WSVOL) tasks. However, state-of-the-art methods only rely on visual and…
Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial Networks
Tehseen Zia, Zeeshan Nisar, Shakeeb Murtaza
The image-based diagnosis is now a vital aspect of modern automation assisted diagnosis. To enable models to produce pixel-level diagnosis, pixel-level ground-truth labels are esse…
Constrained Sampling for Class-Agnostic Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Marco Pedersoli +2
Self-supervised vision transformers can generate accurate localization maps of the objects in an image. However, since they decompose the scene into multiple maps containing variou…
Discriminative Sampling of Proposals in Self-Supervised Transformers for Weakly Supervised Object Localization
Shakeeb Murtaza, Soufiane Belharbi, Marco Pedersoli +2
Drones are employed in a growing number of visual recognition applications. A recent development in cell tower inspection is drone-based asset surveillance, where the autonomous fl…
Text-to-Image Generation with Attention Based Recurrent Neural Networks
Tehseen Zia, Shahan Arif, Shakeeb Murtaza +1
Conditional image modeling based on textual descriptions is a relatively new domain in unsupervised learning. Previous approaches use a latent variable model and generative adversa…