7 citations · 12 across the 12 of their papers we have counts for
12 papers
MV2: Multi-View Multi-Vehicle Driving Dataset for Novel View Synthesis
Sanjay Bhargav Dharavath, Hanvitha Saraswathi Mukkamala, Faizan Farooq Khan +4
Differentiable rendering has advanced novel view synthesis (NVS), yet applying it to real-world driving remains difficult due to sparse capture viewpoints, dynamic objects, and lim…
Step-by-step Layered Design Generation
Faizan Farooq Khan, K J Joseph, Koustava Goswami +2
Design generation, in its essence, is a step-by-step process where designers progressively refine and enhance their work through careful modifications. Despite this fundamental cha…
ReefNet: A Large-Scale Dataset and Benchmark for Fine-Grained Coral Reef Recognition
Abdulwahab Felemban, Yahia Battach, Faizan Farooq Khan +10
Coral reefs are rapidly declining under anthropogenic pressures (e.g., climate change), creating an urgent need for scalable and automated monitoring. Progress in data-driven coral…
FishNet++: Analyzing the capabilities of Multimodal Large Language Models in marine biology
Faizan Farooq Khan, Yousef Radwan, Eslam Abdelrahman +6
Multimodal large language models (MLLMs) have demonstrated impressive cross-domain capabilities, yet their proficiency in specialized scientific fields like marine biology remains…
Category-level Text-to-Image Retrieval Improved: Bridging the Domain Gap with Diffusion Models and Vision Encoders
Faizan Farooq Khan, Vladan Stojnić, Zakaria Laskar +2
This work explores text-to-image retrieval for queries that specify or describe a semantic category. While vision-and-language models (VLMs) like CLIP offer a straightforward open-…
Neural Catalog: Scaling Species Recognition with Catalog of Life-Augmented Generation
Faizan Farooq Khan, Jun Chen, Youssef Mohamed +2
Open-vocabulary species recognition is a major challenge in computer vision, particularly in ornithology, where new taxa are continually discovered. While benchmarks like CUB-200-2…
How Well Can Vision Language Models See Image Details?
Chenhui Gou, Abdulwahab Felemban, Faizan Farooq Khan +4
Large Language Model-based Vision-Language Models (LLM-based VLMs) have demonstrated impressive results in various vision-language understanding tasks. However, how well these VLMs…
AI Art Neural Constellation: Revealing the Collective and Contrastive State of AI-Generated and Human Art
Faizan Farooq Khan, Diana Kim, Divyansh Jha +5
Discovering the creative potentials of a random signal to various artistic expressions in aesthetic and conceptual richness is a ground for the recent success of generative machine…
HRS-Bench: Holistic, Reliable and Scalable Benchmark for Text-to-Image Models
Eslam Mohamed Bakr, Pengzhan Sun, Xiaoqian Shen +3
In recent years, Text-to-Image (T2I) models have been extensively studied, especially with the emergence of diffusion models that achieve state-of-the-art results on T2I synthesis…
It is Okay to Not Be Okay: Overcoming Emotional Bias in Affective Image Captioning by Contrastive Data Collection
Youssef Mohamed, Faizan Farooq Khan, Kilichbek Haydarov +1
Datasets that capture the connection between vision, language, and affection are limited, causing a lack of understanding of the emotional aspect of human intelligence. As a step i…
Intelligent Video Editing: Incorporating Modern Talking Face Generation Algorithms in a Video Editor
Anchit Gupta, Faizan Farooq Khan, Rudrabha Mukhopadhyay +2
This paper proposes a video editor based on OpenShot with several state-of-the-art facial video editing algorithms as added functionalities. Our editor provides an easy-to-use inte…
Generating Dataset For Large-scale 3D Facial Emotion Recognition
Faizan Farooq Khan, Syed Zulqarnain Gilani
The tremendous development in deep learning has led facial expression recognition (FER) to receive much attention in the past few years. Although 3D FER has an inherent edge over i…