activity
20162026
most citedBinary Patterns Encoded Convolutional Neural Networks for Texture Recognition and Remote Sensing Scene Classification

289 citations · 655 across the 80 of their papers we have counts for

collaborators

92 papers

cs.CV2026

AgroGround: Multi-Granularity Grounded Recognition in Agriculture

Abdulla Alshehhi, Zongyan Han, Rao Muhammad Anwer +1

Agricultural visual models are typically evaluated for either recognition or localization, but reliable diagnosis requires identifying what is present and localizing the evidence.…

cs.CV2026

Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings

Chao Qin, Fahad Shahbaz Khan, Salman Khan +4

Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when device, operator, or anatomy cha…

cs.CV2026

Gaussian-JEPA: Joint-Embedding Predictive Learning for 3D Gaussian Splats

Bin Ren, Qi Ma, Yue Li +7

3D Gaussian Splatting (3DGS) represents 3D content with anisotropic primitives that jointly encode geometry and appearance. Fixed-budget encoders consume sampled observations of Ga…

cs.CV2026

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

Amol Harsh, Zongyan Han, Jean Lahoud +5

Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to the referred 3D region, whil…

cs.CV2026

MAviS: A Multimodal Conversational Assistant For Avian Species

Yevheniia Kryklyvets, Mohammed Irfan Kurpath, Sahal Shaji Mullappilly +5

Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monitoring. However, existing multimo…

cs.CV2026

Audit After Segmentation: Reference-Free Mask Quality Assessment for Language-Referred Audio-Visual Segmentation

Jinxing Zhou, Yanghao Zhou, Yaoting Wang +5

Language-referred audio-visual segmentation (Ref-AVS) aims to segment target objects described by natural language by jointly reasoning over video, audio, and text. Beyond generati…

cs.CV2026

DuwatBench: Bridging Language and Visual Heritage through an Arabic Calligraphy Benchmark for Multimodal Understanding

Shubham Patle, Sara Ghaboura, Hania Tariq +4

Arabic calligraphy represents one of the richest visual traditions of the Arabic language, blending linguistic meaning with artistic form. Although multimodal models have advanced…

cs.CV2025

A Benchmark for Omni-Modal Reasoning in Long Videos

Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan, Jinxing Zhou +12

Long-form omni-modal video understanding requires integrating vision, speech, and ambient audio with coherent long-context reasoning. Existing video benchmarks often trade off temp…

cs.CV2025

MedROV: Towards Real-Time Open-Vocabulary Detection Across Diverse Medical Imaging Modalities

Tooba Tehreem Sheikh, Jean Lahoud, Rao Muhammad Anwer +3

Traditional object detection models in medical imaging operate within a closed-set paradigm, limiting their ability to detect objects of novel labels. Open-vocabulary object detect…

cs.CV2025

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards

Omkar Thawakar, Shravan Venkatraman, Ritesh Thawkar +5

Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines still depend on human-curated dat…

cs.CV2025

DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models

Komal Kumar, Rao Muhammad Anwer, Fahad Shahbaz Khan +3

Efficient fine-tuning of pre-trained Text-to-Image (T2I) models involves adjusting the model to suit a particular task or dataset while minimizing computational resources and limit…

cs.CV2025

How Good are Foundation Models in Step-by-Step Embodied Reasoning?

Dinura Dissanayake, Ahmed Heakl, Omkar Thawakar +9

Embodied agents operating in the physical world must make decisions that are not only effective but also safe, spatially coherent, and grounded in context. While recent advances in…

cs.CV2025

Beyond Simple Edits: Composed Video Retrieval with Dense Modifications

Omkar Thawakar, Dmitry Demidov, Ritesh Thawkar +4

Composed video retrieval is a challenging task that strives to retrieve a target video based on a query video and a textual description detailing specific modifications. Standard r…

cs.MM2025

Think Before You Segment: An Object-aware Reasoning Agent for Referring Audio-Visual Segmentation

Jinxing Zhou, Yanghao Zhou, Mingfei Han +4

Referring Audio-Visual Segmentation (Ref-AVS) aims to segment target objects in audible videos based on given reference expressions. Prior works typically rely on learning latent e…

cs.CV2025

RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping

Dongming Wu, Yanping Fu, Saike Huang +8

General robotic grasping systems require accurate object affordance perception in diverse open-world scenarios following human instructions. However, current studies suffer from th…

cs.CV2025

All in One: Visual-Description-Guided Unified Point Cloud Segmentation

Zongyan Han, Mohamed El Amine Boudjoghra, Jiahua Dong +2

Unified segmentation of 3D point clouds is crucial for scene understanding, but is hindered by its sparse structure, limited annotations, and the challenge of distinguishing fine-g…

cs.CV2025

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock

Umair Nawaz, Muhammad Zaigham Zaheer, Ufaq Khan +4

Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sectors face considerable challenge…

cs.CV2025★ 1 cited

TerraFM: A Scalable Foundation Model for Unified Multisensor Earth Observation

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

Modern Earth observation (EO) increasingly leverages deep learning to harness the scale and diversity of satellite imagery across sensors and regions. While recent foundation model…

cs.CV2025

TAViS: Text-bridged Audio-Visual Segmentation with Foundation Models

Ziyang Luo, Nian Liu, Xuguang Yang +5

Audio-Visual Segmentation (AVS) faces a fundamental challenge of effectively aligning audio and visual modalities. While recent approaches leverage foundation models to address dat…

cs.CL2025

Fann or Flop: A Multigenre, Multiera Benchmark for Arabic Poetry Understanding in LLMs

Wafa Alghallabi, Ritesh Thawkar, Sara Ghaboura +5

Arabic poetry is one of the richest and most culturally rooted forms of expression in the Arabic language, known for its layered meanings, stylistic diversity, and deep historical…

cs.CV2025

ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark

Sara Ghaboura, Ketan More, Wafa Alghallabi +5

As Large Multimodal Models (LMMs) become more capable, there is growing interest in evaluating their reasoning processes alongside their final outputs. However, most benchmarks rem…

cs.CV2025

Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks

Tajamul Ashraf, Amal Saqib, Hanan Ghani +11

Deep reasoning is fundamental for solving complex tasks, especially in vision-centric scenarios that demand sequential, multimodal understanding. However, existing benchmarks typic…

cs.CV2025

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning

Zongyan Han, Jiale Cao, Shuo Chen +3

Open-Vocabulary Segmentation (OVS) has drawn increasing attention for its capacity to generalize segmentation beyond predefined categories. However, existing methods typically pred…

cs.CV2025

Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining

Qi Fan, Kaiqi Liu, Nian Liu +4

Cross-domain few-shot segmentation (CD-FSS) aims to segment objects of novel classes in new domains, which is often challenging due to the diverse characteristics of target domains…