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cs.CV updates on arXiv.org

ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents On the Robustness of Watermarking for Autoregressive Image Generation Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference Anthropogenic Regional Adaptation in Multimodal Vision-Language Model From Redaction to Restoration: Deep Learning for Medical Image Anonymization and Reconstruction The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning Semantic-Geometric Dual Compression: Training-Free Visual Token Reduction for Ultra-High-Resolution Remote Sensing Understanding Lightweight Low-Light Image Enhancement via Distribution-Normalizing Preprocessing and Depthwise U-Net Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Evaluating the Impact of Medical Image Reconstruction on Downstream AI Fairness and Performance Retinal Cyst Detection from Optical Coherence Tomography Images LoViF 2026 The First Challenge on Weather Removal in Videos STORM: End-to-End Referring Multi-Object Tracking in Videos Data-Efficient Surgical Phase Segmentation in Small-Incision Cataract Surgery: A Controlled Study of Vision Foundation Models Rethinking the Diffusion Model from a Langevin Perspective Zero-shot World Models Are Developmentally Efficient Learners Edu-MMBias: A Three-Tier Multimodal Benchmark for Auditing Social Bias in Vision-Language Models under Educational Contexts VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation Degradation-Consistent Paired Training for Robust AI-Generated Image Detection FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer Demographic and Linguistic Bias Evaluation in Omnimodal Language Models FlowPalm: Optical Flow Driven Non-Rigid Deformation for Geometrically Diverse Palmprint Generation Cross-Cultural Value Awareness in Large Vision-Language Models I Walk the Line: Examining the Role of Gestalt Continuity in Object Binding for Vision Transformers GLEaN: A Text-to-image Bias Detection Approach for Public Comprehension From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping Not Your Stereo-Typical Estimator: Combining Vision and Language for Volume Perception Genie 4D: Semantic-Prior-Guided 4D Dynamic Scene Reconstruction Efficient Personalization of Generative User Interfaces Is There Knowledge Left to Extract? Evidence of Fragility in Medically Fine-Tuned Vision-Language Models ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories PhysInOne: Visual Physics Learning and Reasoning in One Suite Through Their Eyes: Fixation-aligned Tuning for Personalized User Emulation Neural Distribution Prior for LiDAR Out-of-Distribution Detection Adding Another Dimension to Image-based Animal Detection Long-SCOPE: Fully Sparse Long-Range Cooperative 3D Perception CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation FIRE-CIR: Fine-grained Reasoning for Composed Fashion Image Retrieval Detecting Diffusion-generated Images via Dynamic Assembly Forests Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation Tora3: Trajectory-Guided Audio-Video Generation with Physical Coherence Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion Dynamic Class-Aware Active Learning for Unbiased Satellite Image Segmentation Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift Degradation-Robust Fusion: An Efficient Degradation-Aware Diffusion Framework for Multimodal Image Fusion in Arbitrary Degradation Scenarios Adaptive Dual Residual U-Net with Attention Gate and Multiscale Spatial Attention Mechanisms (ADRUwAMS) MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification BIAS: A Biologically Inspired Algorithm for Video Saliency Detection DeFakeQ: Enabling Real-Time Deepfake Detection on Edge Devices via Adaptive Bidirectional Quantization Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs CatalogStitch: Dimension-Aware and Occlusion-Preserving Object Compositing for Catalog Image Generation Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning SenBen: Sensitive Scene Graphs for Explainable Content Moderation Towards Responsible Multimodal Medical Reasoning via Context-Aligned Vision-Language Models R2G: A Multi-View Circuit Graph Benchmark Suite from RTL to GDSII State Space Models are Effective Sign Language Learners: Exploiting Phonological Compositionality for Vocabulary-Scale Recognition Accelerating Transformer-Based Monocular SLAM via Geometric Utility Scoring Deep Learning-Based Tracking and Lineage Reconstruction of Ligament Breakup Unified Multimodal Uncertain Inference Unsupervised Local Plasticity in a Multi-Frequency VisNet Hierarchy EfficientSign: An Attention-Enhanced Lightweight Architecture for Indian Sign Language Recognition InsEdit: Towards Instruction-based Visual Editing via Data-Efficient Video Diffusion Models Adaptation 3D-VCD: Hallucination Mitigation in 3D-LLM Embodied Agents through Visual Contrastive Decoding On Semiotic-Grounded Interpretive Evaluation of Generative Art Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting From Selection to Scheduling: Federated Geometry-Aware Correction Makes Exemplar Replay Work Better under Continual Dynamic Heterogeneity ViSAGE @ NTIRE 2026 Challenge on Video Saliency Prediction Needle in a Haystack: One-Class Representation Learning for Detecting Rare Malignant Cells in Computational Cytology A Semi-Automated Framework for 3D Reconstruction of Medieval Manuscript Miniatures Detection of Hate and Threat in Digital Forensics: A Case-Driven Multimodal Approach Orthogonal Quadratic Complements for Vision Transformer Feed-Forward Networks HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models Pretrain-then-Adapt: Uncertainty-Aware Test-Time Adaptation for Text-based Person Search Assessing Privacy Preservation and Utility in Online Vision-Language Models R3PM-Net: Real-time, Robust, Real-world Point Matching Network Tipiano: Cascaded Piano Hand Motion Synthesis via Fingertip Priors Belief-Aware VLM Model for Human-like Reasoning GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents B-MoE: A Body-Part-Aware Mixture-of-Experts "All Parts Matter" Approach to Micro-Action Recognition FDIF: Formula-Driven supervised Learning with Implicit Functions for 3D Medical Image Segmentation CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention BiCLIP: Domain Canonicalization via Structured Geometric Transformation Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers When & How to Write for Personalized Demand-aware Query Rewriting in Video Search Relational Visual Similarity Enhancing Geo-localization for Crowdsourced Flood Imagery via LLM-Guided Attention GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models OmniPrism: Learning Disentangled Visual Concept for Image Generation MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions
Vines-DB: An RGB image dataset for multi-species ornamental vine segmentation
[Submitted on 16 Jun 2026] · 2026-06-18 · via cs.CV updates on arXiv.org

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Abstract:The Vines-DB dataset contains 1,218 original high-resolution RGB images of seven ornamental vine species collected under field conditions at the Utah Agricultural Experiment Station's Greenville Research Farm in Logan, Utah, USA. The dataset was generated from 168 individual vine plants that were transplanted in 2022 and photographed repeatedly across multiple months during the 2023 and 2024 growing seasons (July-October). Images were captured with an iPhone 16 Pro equipped with a 48 MP camera between 10:00 AM and 12:00 PM under daylight. Vines were grown on 1.2m x 2.4m trellises and photographed from a distance of 1m against black or white Styrofoam backdrops to improve contrast and reduce background noise. The dataset includes Akebia quinata, Campsis radicans, Hydrangea anomala petiolaris, Lonicera x heckrottii, Campsis x tagliabuana 'Madame Galen', Parthenocissus quinquefolia, and Wisteria floribunda. All original images were manually annotated in Roboflow by trained annotators to produce polygon-based instance segmentation masks for eight classes, including seven species and background. After preprocessing and data augmentation, the working dataset was expanded to 2,307 images for model development and evaluation. The augmented dataset was divided into 2,019 training images, 192 validation images, and 96 test images using stratified sampling to maintain balanced representation. Vines-DB supports the development and evaluation of deep learning models for multi-class instance segmentation in precision horticulture and urban ecology. The dataset enables applications such as automated canopy cover estimation, species identification, and scalable field phenotyping. In addition, repeated monthly imaging of the plants captures temporal variation in canopy development and plant appearance, increasing the dataset's utility for segmentation benchmarking under realistic field conditions.

Submission history

From: Saroj Burlakoti [view email]
[v1] Tue, 16 Jun 2026 20:52:15 UTC (622 KB)