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20202026
most citedLatent Embedding Feedback and Discriminative Features for Zero-Shot Classification

33 citations · 133 across the 57 of their papers we have counts for

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49 papers · 1 filter

cs.CV2026

MediX-R1: Open Ended Medical Reinforcement Learning

Sahal Shaji Mullappilly, Mohammed Irfan Kurpath, Omair Mohamed +5

We introduce MediX-R1, an open-ended Reinforcement Learning (RL) framework for medical multimodal large language models (MLLMs) that enables clinically grounded, free-form answers…

cs.CV2025★ 1 cited

GenZSL: Generative Zero-Shot Learning Via Inductive Variational Autoencoder

Shiming Chen, Dingjie Fu, Salman Khan +1

Remarkable progress in zero-shot learning (ZSL) has been achieved using generative models. However, existing generative ZSL methods merely generate (imagine) the visual features fr…

cs.CV2025★ 1 cited

ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Tasks

Akashah Shabbir, Muhammad Akhtar Munir, Akshay Dudhane +6

Recent progress in large language models (LLMs) has enabled tool-augmented agents capable of solving complex real-world tasks through step-by-step reasoning. However, existing eval…

cs.CV2025

Deep Learning in Concealed Dense Prediction

Pancheng Zhao, Deng-Ping Fan, Shupeng Cheng +5

Deep learning is developing rapidly and handling common computer vision tasks well. It is time to pay attention to more complex vision tasks, as model size, knowledge, and reasonin…

cs.CV2025

DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model for Driving Scenario Understanding

Ayesha Ishaq, Jean Lahoud, Ketan More +10

While large multimodal models (LMMs) have demonstrated strong performance across various Visual Question Answering (VQA) tasks, certain challenges require complex multi-step reason…

cs.CV2025

Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology

Hashmat Shadab Malik, Shahina Kunhimon, Muzammal Naseer +2

Adversarial attacks pose significant challenges for vision models in critical fields like healthcare, where reliability is essential. Although adversarial training has been well st…

cs.CV2025

C-Drag: Chain-of-Thought Driven Motion Controller for Video Generation

Yuhao Li, Mirana Claire Angel, Salman Khan +4

Trajectory-based motion control has emerged as an intuitive and efficient approach for controllable video generation. However, the existing trajectory-based approaches are usually…

cs.CV2025

Time Travel: A Comprehensive Benchmark to Evaluate LMMs on Historical and Cultural Artifacts

Sara Ghaboura, Ketan More, Ritesh Thawkar +6

Understanding historical and cultural artifacts demands human expertise and advanced computational techniques, yet the process remains complex and time-intensive. While large multi…

cs.CV2025

AIN: The Arabic INclusive Large Multimodal Model

Ahmed Heakl, Sara Ghaboura, Omkar Thawkar +4

Amid the swift progress of large language models (LLMs) and their evolution into large multimodal models (LMMs), significant strides have been made in high-resource languages such…

cs.CV2025★ 1 cited

Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language Models

Hashmat Shadab Malik, Fahad Shamshad, Muzammal Naseer +3

Multi-modal Large Language Models (MLLMs) excel in vision-language tasks but remain vulnerable to visual adversarial perturbations that can induce hallucinations, manipulate respon…

cs.CV2025★ 1 cited

GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing

Akashah Shabbir, Mohammed Zumri, Mohammed Bennamoun +2

Recent advances in large multimodal models (LMMs) have recognized fine-grained grounding as an imperative factor of visual understanding and dialogue. However, the benefits of such…

cs.CV2024

Discriminative Image Generation with Diffusion Models for Zero-Shot Learning

Dingjie Fu, Wenjin Hou, Shiming Chen +4

Generative Zero-Shot Learning (ZSL) methods synthesize class-related features based on predefined class semantic prototypes, showcasing superior performance. However, this feature…

cs.CV2024

UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities

Muhammad Uzair Khattak, Shahina Kunhimon, Muzammal Naseer +2

Vision-Language Models (VLMs) trained via contrastive learning have achieved notable success in natural image tasks. However, their application in the medical domain remains limite…

cs.CV2024

EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues

Sagar Soni, Akshay Dudhane, Hiyam Debary +8

Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and {r…

cs.CV2024

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks

Muhammad Sohail Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah +5

While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they do not effectively address the specific challenges of geospatial applications. Gene…

cs.CV2024★ 1 cited

VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos

Shehan Munasinghe, Hanan Gani, Wenqi Zhu +4

Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle bas…

cs.CV2024

CAMEL-Bench: A Comprehensive Arabic LMM Benchmark

Sara Ghaboura, Ahmed Heakl, Omkar Thawakar +7

Recent years have witnessed a significant interest in developing large multimodal models (LMMs) capable of performing various visual reasoning and understanding tasks. This has led…

cs.CV2024

How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization?

Jiahua Dong, Wenqi Liang, Hongliu Li +5

Custom diffusion models (CDMs) have attracted widespread attention due to their astonishing generative ability for personalized concepts. However, most existing CDMs unreasonably a…

cs.CV2024★ 2 cited

AgriCLIP: Adapting CLIP for Agriculture and Livestock via Domain-Specialized Cross-Model Alignment

Umair Nawaz, Muhammad Awais, Hanan Gani +4

Capitalizing on vast amount of image-text data, large-scale vision-language pre-training has demonstrated remarkable zero-shot capabilities and has been utilized in several applica…

cs.CV2024

Open3DTrack: Towards Open-Vocabulary 3D Multi-Object Tracking

Ayesha Ishaq, Mohamed El Amine Boudjoghra, Jean Lahoud +4

3D multi-object tracking plays a critical role in autonomous driving by enabling the real-time monitoring and prediction of multiple objects' movements. Traditional 3D tracking sys…

cs.CV2024★ 1 cited

CDChat: A Large Multimodal Model for Remote Sensing Change Description

Mubashir Noman, Noor Ahsan, Muzammal Naseer +4

Large multimodal models (LMMs) have shown encouraging performance in the natural image domain using visual instruction tuning. However, these LMMs struggle to describe the content…

cs.CV2024

BAPLe: Backdoor Attacks on Medical Foundational Models using Prompt Learning

Asif Hanif, Fahad Shamshad, Muhammad Awais +5

Medical foundation models are gaining prominence in the medical community for their ability to derive general representations from extensive collections of medical image-text pairs…

cs.CV2024

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…

cs.CV2024★ 7 cited

VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding

Muhammad Maaz, Hanoona Rasheed, Salman Khan +1

Building on the advances of language models, Large Multimodal Models (LMMs) have contributed significant improvements in video understanding. While the current video LMMs utilize a…