activity
20182023
most citedMask-Guided Attention Network for Occluded Pedestrian Detection

36 citations · 78 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

15 papers · 1 filter

cs.CV2023

Domain Adaptive Object Detection via Balancing Between Self-Training and Adversarial Learning

Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz +1

Deep learning based object detectors struggle generalizing to a new target domain bearing significant variations in object and background. Most current methods align domains by usi…

cs.CV2023

Generalizing Across Domains in Diabetic Retinopathy via Variational Autoencoders

Sharon Chokuwa, Muhammad H. Khan

Domain generalization for Diabetic Retinopathy (DR) classification allows a model to adeptly classify retinal images from previously unseen domains with various imaging conditions…

cs.CV20232 cited

Unsupervised Landmark Discovery Using Consistency Guided Bottleneck

Mamona Awan, Muhammad Haris Khan, Sanoojan Baliah +4

We study a challenging problem of unsupervised discovery of object landmarks. Many recent methods rely on bottlenecks to generate 2D Gaussian heatmaps however, these are limited in…

cs.CV2023

Multiclass Alignment of Confidence and Certainty for Network Calibration

Vinith Kugathasan, Muhammad Haris Khan

Deep neural networks (DNNs) have made great strides in pushing the state-of-the-art in several challenging domains. Recent studies reveal that they are prone to making overconfiden…

cs.CV20232 cited

Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic Retinopathy

Sanoojan Baliah, Fadillah A. Maani, Santosh Sanjeev +1

Diabetic Retinopathy (DR), a leading cause of vision impairment, requires early detection and treatment. Developing robust AI models for DR classification holds substantial potenti…

cs.CV2023

Unsupervised Deep Graph Matching Based on Cycle Consistency

Siddharth Tourani, Carsten Rother, Muhammad Haris Khan +1

We contribute to the sparsely populated area of unsupervised deep graph matching with application to keypoint matching in images. Contrary to the standard \emph{supervised} approac…