3.6k citations · 4.8k across the 50 of their papers we have counts for
16 papers · 1 filter
MARLIN: Masked Autoencoder for facial video Representation LearnINg
Zhixi Cai, Shreya Ghosh, Kalin Stefanov +5
This paper proposes a self-supervised approach to learn universal facial representations from videos, that can transfer across a variety of facial analysis tasks such as Facial Att…
LAVA: Label-efficient Visual Learning and Adaptation
Islam Nassar, Munawar Hayat, Ehsan Abbasnejad +3
We present LAVA, a simple yet effective method for multi-domain visual transfer learning with limited data. LAVA builds on a few recent innovations to enable adapting to partially…
CLIP model is an Efficient Continual Learner
Vishal Thengane, Salman Khan, Munawar Hayat +1
The continual learning setting aims to learn new tasks over time without forgetting the previous ones. The literature reports several significant efforts to tackle this problem wit…
Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation
Himashi Peiris, Munawar Hayat, Zhaolin Chen +2
As intensities of MRI volumes are inconsistent across institutes, it is essential to extract universal features of multi-modal MRIs to precisely segment brain tumors. In this conce…
Concealing Sensitive Samples against Gradient Leakage in Federated Learning
Jing Wu, Munawar Hayat, Mingyi Zhou +1
Federated Learning (FL) is a distributed learning paradigm that enhances users privacy by eliminating the need for clients to share raw, private data with the server. Despite the s…
'Labelling the Gaps': A Weakly Supervised Automatic Eye Gaze Estimation
Shreya Ghosh, Abhinav Dhall, Jarrod Knibbe +1
Over the past few years, there has been an increasing interest to interpret gaze direction in an unconstrained environment with limited supervision. Owing to data curation and anno…
AV-Gaze: A Study on the Effectiveness of Audio Guided Visual Attention Estimation for Non-Profilic Faces
Shreya Ghosh, Abhinav Dhall, Munawar Hayat +1
In challenging real-life conditions such as extreme head-pose, occlusions, and low-resolution images where the visual information fails to estimate visual attention/gaze direction,…
Transformer Scale Gate for Semantic Segmentation
Hengcan Shi, Munawar Hayat, Jianfei Cai
Effectively encoding multi-scale contextual information is crucial for accurate semantic segmentation. Existing transformer-based segmentation models combine features across scales…
NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
Yawei Li, Kai Zhang, Radu Timofte +108
This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…
Learning Enriched Features for Fast Image Restoration and Enhancement
Syed Waqas Zamir, Aditya Arora, Salman Khan +4
Given a degraded input image, image restoration aims to recover the missing high-quality image content. Numerous applications demand effective image restoration, e.g., computationa…
Semantic-Aware Domain Generalized Segmentation
Duo Peng, Yinjie Lei, Munawar Hayat +2
Deep models trained on source domain lack generalization when evaluated on unseen target domains with different data distributions. The problem becomes even more pronounced when we…
Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localization
Zhixi Cai, Kalin Stefanov, Abhinav Dhall +1
Due to its high societal impact, deepfake detection is getting active attention in the computer vision community. Most deepfake detection methods rely on identity, facial attribute…
Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds
Zhao Jin, Yinjie Lei, Naveed Akhtar +2
Point cloud scene flow estimation is of practical importance for dynamic scene navigation in autonomous driving. Since scene flow labels are hard to obtain, current methods train t…
Transformers in Medical Imaging: A Survey
Fahad Shamshad, Salman Khan, Syed Waqas Zamir +4
Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results a…
ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues
Hengcan Shi, Munawar Hayat, Yicheng Wu +1
Object proposal generation is an important and fundamental task in computer vision. In this paper, we propose ProposalCLIP, a method towards unsupervised open-category object propo…
Unpaired Referring Expression Grounding via Bidirectional Cross-Modal Matching
Hengcan Shi, Munawar Hayat, Jianfei Cai
Referring expression grounding is an important and challenging task in computer vision. To avoid the laborious annotation in conventional referring grounding, unpaired referring gr…