b'Salman Khan'

research

∙ 09/19/2023

Unsupervised Landmark Discovery Using Consistency Guided Bottleneck

We study a challenging problem of unsupervised discovery of object landm...

0 Mamona Awan, et al. ∙

research

∙ 08/11/2023

Towards Instance-adaptive Inference for Federated Learning

Federated learning (FL) is a distributed learning paradigm that enables ...

0 Chun-Mei Feng, et al. ∙

research

∙ 08/11/2023

Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning

Benefiting from prompt tuning, recent years have witnessed the promising...

0 Chun-Mei Feng, et al. ∙

research

∙ 07/27/2023

How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges

Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT...

0 Haotong Qin, et al. ∙

research

∙ 07/14/2023

Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation

It is imperative to ensure the robustness of deep learning models in cri...

0 Asif Hanif, et al. ∙

research

∙ 07/13/2023

Video-FocalNets: Spatio-Temporal Focal Modulation for Video Action Recognition

Recent video recognition models utilize Transformer models for long-rang...

0 Syed Talal Wasim, et al. ∙

research

∙ 06/22/2023

PromptIR: Prompting for All-in-One Blind Image Restoration

Image restoration involves recovering a high-quality clean image from it...

0 Vaishnav Potlapalli, et al. ∙

research

∙ 06/15/2023

Learnable Weight Initialization for Volumetric Medical Image Segmentation

Hybrid volumetric medical image segmentation models, combining the advan...

0 Shahina Kunhimon, et al. ∙

research

∙ 06/13/2023

XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models

The latest breakthroughs in large vision-language models, such as Bard a...

9 Omkar Thawkar, et al. ∙

research

∙ 06/08/2023

Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Conversation agents fueled by Large Language Models (LLMs) are providing...

0 Muhammad Maaz, et al. ∙

research

∙ 05/26/2023

Modulate Your Spectrum in Self-Supervised Learning

Whitening loss provides theoretical guarantee in avoiding feature collap...

0 Xi Weng, et al. ∙

research

∙ 04/30/2023

Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection

Most previous co-salient object detection works mainly focus on extracti...

1 Long Li, et al. ∙

research

∙ 04/13/2023

Remote Sensing Change Detection With Transformers Trained from Scratch

Current transformer-based change detection (CD) approaches either employ...

5 Mubashir Noman, et al. ∙

research

∙ 04/13/2023

Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement

Burst image processing is becoming increasingly popular in recent years....

0 Nancy Mehta, et al. ∙

research

∙ 04/06/2023

Vita-CLIP: Video and text adaptive CLIP via Multimodal Prompting

Adopting contrastive image-text pretrained models like CLIP towards vide...

0 Syed Talal Wasim, et al. ∙

research

∙ 04/03/2023

Video Instance Segmentation in an Open-World

Existing video instance segmentation (VIS) approaches generally follow a...

0 Omkar Thawakar, et al. ∙

research

∙ 03/25/2023

Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection

Deep neural networks (DNNs) have enabled astounding progress in several ...

0 Muhammad Akhtar Munir, et al. ∙

research

∙ 02/23/2023

Boosting Adversarial Transferability using Dynamic Cues

The transferability of adversarial perturbations between image models ha...

0 Muzammal Naseer, et al. ∙

research

∙ 12/30/2022

Guidance Through Surrogate: Towards a Generic Diagnostic Attack

Adversarial training is an effective approach to make deep neural networ...

0 Muzammal Naseer, et al. ∙

research

∙ 12/11/2022

PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category Discovery

Although existing semi-supervised learning models achieve remarkable suc...

0 Sheng Zhang, et al. ∙

research

∙ 12/06/2022

Fine-tuned CLIP Models are Efficient Video Learners

Large-scale multi-modal training with image-text pairs imparts strong ge...

0 Hanoona Rasheed, et al. ∙

research

∙ 11/22/2022

Person Image Synthesis via Denoising Diffusion Model

The pose-guided person image generation task requires synthesizing photo...

0 Ankan Kumar Bhunia, et al. ∙

research

∙ 10/07/2022

An Investigation into Whitening Loss for Self-supervised Learning

A desirable objective in self-supervised learning (SSL) is to avoid feat...

8 Xi Weng, et al. ∙

research

∙ 10/06/2022

MaPLe: Multi-modal Prompt Learning

Pre-trained vision-language (V-L) models such as CLIP have shown excelle...

3 Muhammad Uzair Khattak, et al. ∙

research

∙ 10/06/2022

CLIP model is an Efficient Continual Learner

The continual learning setting aims to learn new tasks over time without...

0 Vishal Thengane, et al. ∙

research

∙ 10/04/2022

ROAD-R: The Autonomous Driving Dataset with Logical Requirements

Neural networks have proven to be very powerful at computer vision tasks...

0 Eleonora Giunchiglia, et al. ∙

research

∙ 09/12/2022

Identification of Cognitive Workload during Surgical Tasks with Multimodal Deep Learning

The operating room (OR) is a dynamic and complex environment consisting ...

8 Kaizhe Jin, et al. ∙

research

∙ 09/12/2022

Situation Awareness for Automated Surgical Check-listing in AI-Assisted Operating Room

Nowadays, there are more surgical procedures that are being performed us...

12 Tochukwu Onyeogulu, et al. ∙

research

∙ 09/02/2022

Transformers in Remote Sensing: A Survey

Deep learning-based algorithms have seen a massive popularity in differe...

2 Abdulaziz Amer Aleissaee, et al. ∙

research

∙ 08/14/2022

AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility

One of the key factors behind the recent success in visual tracking is t...

5 Mubashir Noman, et al. ∙

research

∙ 07/25/2022

Self-Distilled Vision Transformer for Domain Generalization

In recent past, several domain generalization (DG) methods have been pro...

3 Maryam Sultana, et al. ∙

research

∙ 07/18/2022

Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations

Transferable adversarial attacks optimize adversaries from a pretrained ...

3 Hashmat Shadab Malik, et al. ∙

research

∙ 07/07/2022

Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection

Existing open-vocabulary object detectors typically enlarge their vocabu...

8 Hanoona Rasheed, et al. ∙

research

∙ 07/05/2022

OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning

Semi-supervised learning (SSL) is one of the dominant approaches to addr...

10 Mamshad Nayeem Rizve, et al. ∙

research

∙ 06/21/2022

EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications

In the pursuit of achieving ever-increasing accuracy, large and complex ...

18 Muhammad Maaz, et al. ∙

research

∙ 04/22/2022

Self-Supervised Video Object Segmentation via Cutout Prediction and Tagging

We propose a novel self-supervised Video Object Segmentation (VOS) appro...

0 jyoti-kini, et al. ∙

research

∙ 03/28/2022

Energy-based Latent Aligner for Incremental Learning

Deep learning models tend to forget their earlier knowledge while increm...

8 K J Joseph, et al. ∙

research

∙ 03/24/2022

Video Instance Segmentation via Multi-scale Spatio-temporal Split Attention Transformer

State-of-the-art transformer-based video instance segmentation (VIS) app...

9 Omkar Thawakar, et al. ∙

research

∙ 01/24/2022

Transformers in Medical Imaging: A Survey

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

36 Fahad Shamshad, et al. ∙

research

∙ 01/10/2022

Vision in adverse weather: Augmentation using CycleGANs with various object detectors for robust perception in autonomous racing

In an autonomous driving system, perception - identification of features...

5 Izzeddin Teeti, et al. ∙

research

∙ 01/07/2022

A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items

Screening cluttered and occluded contraband items from baggage X-ray sca...

6 Taimur Hassan, et al. ∙

research

∙ 12/09/2021

Spatio-temporal Relation Modeling for Few-shot Action Recognition

We propose a novel few-shot action recognition framework, STRM, which en...

6 Anirudh Thatipelli, et al. ∙

research

∙ 12/06/2021

DoodleFormer: Creative Sketch Drawing with Transformers

Creative sketching or doodling is an expressive activity, where imaginat...

0 Ankan Kumar Bhunia, et al. ∙

research

∙ 12/02/2021

Self-supervised Video Transformer

In this paper, we propose self-supervised training for video transformer...

0 Kanchana Ranasinghe, et al. ∙

research

∙ 12/02/2021

OW-DETR: Open-world Detection Transformer

Open-world object detection (OWOD) is a challenging computer vision prob...

3 Akshita Gupta, et al. ∙

research

∙ 10/27/2021

International Workshop on Continual Semi-Supervised Learning: Introduction, Benchmarks and Baselines

The aim of this paper is to formalize a new continual semi-supervised le...

0 Ajmal Shahbaz, et al. ∙

research

∙ 08/22/2021

Tensor Pooling Driven Instance Segmentation Framework for Baggage Threat Recognition

Automated systems designed for screening contraband items from the X-ray...

2 Taimur Hassan, et al. ∙

research

∙ 08/20/2021

Discriminative Region-based Multi-Label Zero-Shot Learning

Multi-label zero-shot learning (ZSL) is a more realistic counter-part of...

7 Sanath Narayan, et al. ∙

research

∙ 07/23/2021

Learning Discriminative Representations for Multi-Label Image Recognition

Multi-label recognition is a fundamental, and yet is a challenging task ...

17 Mohammed Hassanin, et al. ∙

research

∙ 07/15/2021

Unsupervised Anomaly Instance Segmentation for Baggage Threat Recognition

Identifying potential threats concealed within the baggage is of prime c...

0 Taimur Hassan, et al. ∙

Salman Khan

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