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20192026
most citedTransformers in Vision: A Survey

3.6k citations · 4.2k across the 22 of their papers we have counts for

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17 papers · 1 filter

cs.CV2024★ 3 cited

Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image Restoration

Akshay Dudhane, Omkar Thawakar, Syed Waqas Zamir +3

All-in-one image restoration tackles different types of degradations with a unified model instead of having task-specific, non-generic models for each degradation. The requirement…

cs.CV2024★ 9 cited

AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation

Yuning Cui, Syed Waqas Zamir, Salman Khan +3

In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent lim…

cs.CV2023★ 35 cited

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

Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan +1

Image restoration involves recovering a high-quality clean image from its degraded version. Deep learning-based methods have significantly improved image restoration performance, h…

cs.CV2023

Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement

Nancy Mehta, Akshay Dudhane, Subrahmanyam Murala +3

Burst image processing is becoming increasingly popular in recent years. However, it is a challenging task since individual burst images undergo multiple degradations and often hav…

cs.CV2023★ 2 cited

Burstormer: Burst Image Restoration and Enhancement Transformer

Akshay Dudhane, Syed Waqas Zamir, Salman Khan +2

On a shutter press, modern handheld cameras capture multiple images in rapid succession and merge them to generate a single image. However, individual frames in a burst are misalig…

cs.CV2022★ 20 cited

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

Muhammad Maaz, Abdelrahman Shaker, Hisham Cholakkal +4

In the pursuit of achieving ever-increasing accuracy, large and complex neural networks are usually developed. Such models demand high computational resources and therefore cannot…

cs.CV2022

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…

cs.CV2021★ 195 cited

Restormer: Efficient Transformer for High-Resolution Image Restoration

Syed Waqas Zamir, Aditya Arora, Salman Khan +3

Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoratio…

cs.CV2021

Burst Image Restoration and Enhancement

Akshay Dudhane, Syed Waqas Zamir, Salman Khan +2

Modern handheld devices can acquire burst image sequence in a quick succession. However, the individual acquired frames suffer from multiple degradations and are misaligned due to…

cs.CV2021★ 54 cited

Multi-Stage Progressive Image Restoration

Syed Waqas Zamir, Aditya Arora, Salman Khan +4

Image restoration tasks demand a complex balance between spatial details and high-level contextualized information while recovering images. In this paper, we propose a novel synerg…

cs.CV2021★ 5 cited

Low Light Image Enhancement via Global and Local Context Modeling

Aditya Arora, Muhammad Haris, Syed Waqas Zamir +4

Images captured under low-light conditions manifest poor visibility, lack contrast and color vividness. Compared to conventional approaches, deep convolutional neural networks (CNN…

cs.CV2021★ 3.6k cited

Transformers in Vision: A Survey

Salman Khan, Muzammal Naseer, Munawar Hayat +3

Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems. Among their salient…

cs.CV2020

Synthesizing the Unseen for Zero-shot Object Detection

Nasir Hayat, Munawar Hayat, Shafin Rahman +3

The existing zero-shot detection approaches project visual features to the semantic domain for seen objects, hoping to map unseen objects to their corresponding semantics during in…

cs.CV2020★ 20 cited

AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Pengxu Wei, Hannan Lu, Radu Timofte +68

This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…

cs.CV2020★ 67 cited

Learning Enriched Features for Real Image Restoration and Enhancement

Syed Waqas Zamir, Aditya Arora, Salman Khan +4

With the goal of recovering high-quality image content from its degraded version, image restoration enjoys numerous applications, such as in surveillance, computational photography…

cs.CV2019★ 175 cited

iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images

Syed Waqas Zamir, Aditya Arora, Akshita Gupta +7

Existing Earth Vision datasets are either suitable for semantic segmentation or object detection. In this work, we introduce the first benchmark dataset for instance segmentation i…

cs.CV2019★ 17 cited

Learning Digital Camera Pipeline for Extreme Low-Light Imaging

Syed Waqas Zamir, Aditya Arora, Salman Khan +2

In low-light conditions, a conventional camera imaging pipeline produces sub-optimal images that are usually dark and noisy due to a low photon count and low signal-to-noise ratio…