195 citations · 558 across the 14 of their papers we have counts for
18 papers
Reasoning with Image Generation
Nishad Singhi, Hector Garcia Rodriguez, Aditya Arora +2
Chain-of-thought reasoning has revolutionized natural language processing by enabling large language models (LLMs) to decompose problems into intermediate steps before answering. Y…
From Visual Cues to Spoken Narration: Rethinking Audio Description
Akshita Gupta, Aditya Arora, Federico Tombari +2
Audio Description (AD) provides spoken narration of visual events during dialogue gaps, making movies accessible to visually impaired audiences. The problem requires determining bo…
ReCap: Lightweight Referential Grounding for Coherent Story Visualization
Aditya Arora, Akshita Gupta, Pau Rodriguez +1
Story Visualization aims to generate a sequence of images that faithfully depicts a textual narrative that preserve character identity, spatial configuration, and stylistic coheren…
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution
Aditya Arora, Zhengzhong Tu, Yufei Wang +3
In this paper, we propose GuideSR, a novel single-step diffusion-based image super-resolution (SR) model specifically designed to enhance image fidelity. Existing diffusion-based S…
Revisiting Image Fusion for Multi-Illuminant White-Balance Correction
David Serrano-Lozano, Aditya Arora, Luis Herranz +3
White balance (WB) correction in scenes with multiple illuminants remains a persistent challenge in computer vision. Recent methods explored fusion-based approaches, where a neural…
Open-Vocabulary Temporal Action Localization using Multimodal Guidance
Akshita Gupta, Aditya Arora, Sanath Narayan +3
Open-Vocabulary Temporal Action Localization (OVTAL) enables a model to recognize any desired action category in videos without the need to explicitly curate training data for all…
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…
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…
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…
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…
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…
CycleISP: Real Image Restoration via Improved Data Synthesis
Syed Waqas Zamir, Aditya Arora, Salman Khan +4
The availability of large-scale datasets has helped unleash the true potential of deep convolutional neural networks (CNNs). However, for the single-image denoising problem, captur…
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…
AnimalWeb: A Large-Scale Hierarchical Dataset of Annotated Animal Faces
Muhammad Haris Khan, John McDonagh, Salman Khan +5
Being heavily reliant on animals, it is our ethical obligation to improve their well-being by understanding their needs. Several studies show that animal needs are often expressed…
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…
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…
Acoustic Features Fusion using Attentive Multi-channel Deep Architecture
Gaurav Bhatt, Akshita Gupta, Aditya Arora +1
In this paper, we present a novel deep fusion architecture for audio classification tasks. The multi-channel model presented is formed using deep convolution layers where different…