Papers Instance Segmentation
“Instance Segmentation” 태그가 달린 논문 2,537편 · 필터 해제
Rethinking Transfer Learning for Industrial Inspection: DINOv3 vs. ImageNet Pretraining Across RGB and X-ray Tasks
Vision foundation models pretrained on web-scale data have recently shown strong transfer capabilities on many downstream tasks, but their effectiveness for industrial visual inspection remains unclear. Industrial data d…
Semantic SegmentationInstance SegmentationTransfer LearningObject DetectionRecursive Block-Diagonal Coupling for Resource-Efficient Training of Vision Models
Training high-capacity vision models from scratch requires substantial computational resources. To improve training efficiency of a wide target model, existing growth methods often assume the availability of narrower mod…
Instance SegmentationObject DetectionRobotic Strawberry Harvesting with Robust Vision and Deep Reinforcement Learning based Sim-to-Real Control
This study presents a closed-loop robotic strawberry harvesting system that combines a robust vision module, simulation-trained deep reinforcement learning (DRL) control, and ROS-based realrobot execution. For perception…
Reinforcement LearningInstance SegmentationSmartphone-based Circular Plot Sampling for Forest Inventory
Circular sample plots are a cornerstone of forest inventory, yet accurate measurement of tree diameter at breast height (DBH) and spatial location within such plots remains challenging. Conventional approaches rely eithe…
Monocular Depth EstimationInstance SegmentationLighting-aware Unified Model for Instance Segmentation
Foundation models like the Segment Anything Model (SAM) demonstrate impressive zero-shot generalization but frequently degrade under diverse real-world illumination, particularly for instance segmentation. In this work, …
Zero-shot GeneralizationInstance SegmentationCounting Machine Parts
Counting objects in an image is a task applicable across many domains. For instance, crowd counting, inventory counting, and cell counting have been the focus of recent research. The major challenges in estimating the co…
Instance SegmentationCrowd CountingHighly Detailed and Generalizable Broadleaf Tree Crown Instance Segmentation from UAV Imagery
We present a highly detailed instance segmentation model for delineating individual tree crowns in natural broadleaf forests using aerial imagery acquired by unmanned aerial vehicles (UAVs). Tree crown delineation in bro…
Instance SegmentationUrban-ImageNet: A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception
We present Urban-ImageNet, a large-scale multi-modal dataset and evaluation benchmark for urban space perception from user-generated social media imagery. The corpus contains over 2 Million public social media images and…
Cross-Modal RetrievalInstance SegmentationScene ClassificationImage ClassificationVVitCutLER: Towards Unsupervised Object Detection and Segmentation in Videos
Unsupervised pixel-level video understanding remains challenging in real-world scenarios, where motion blur, occlusion, and fast object dynamics often cause temporal drift and flickering pseudo-labels.We propose VVitCutL…
Video Object DetectionInstance SegmentationCan Graphs Help Vision SSMs See Better?
Vision state space models inherit the efficiency and long-range modeling ability of Mamba-style selective scans. However, their performance depends critically on the representation of two-dimensional visual features as o…
Semantic SegmentationInstance SegmentationImage ClassificationLong-range modelingChartREG++: Towards Benchmarking and Improving Chart Referring Expression Grounding under Diverse referring clues and Multi-Target Referring
Referring expression grounding is a core problem in visual grounding and is widely used as a diagnostic of spatial grounding and reasoning in vision and language models, yet most prior work focuses on natural images. In …
Instance SegmentationReferring ExpressionVisual GroundingRAM-H1200: A Unified Evaluation and Dataset on Hand Radiographs for Rheumatoid Arthritis
Rheumatoid arthritis (RA) assessment from hand radiographs requires multi-level analysis and modeling of anatomical structures and fine-grained local pathological changes. However, existing public resources do not suppor…
Instance SegmentationIlov3Splat: Instance-Level Open-Vocabulary 3D Scene Understanding in Gaussian Splatting
We introduce Ilov3Splat, a novel framework for instance-level open-vocabulary 3D scene understanding built on 3D Gaussian Splatting (3D-GS). Most prior work depends on 2D rendering-based matching or point-level semantic …
Instance SegmentationScene UnderstandingAnny-Fit: All-Age Human Mesh Recovery
Recovering 3D human pose and shape from a single image remains a cornerstone of human-centric vision, yet most methods assume adult subjects and optimize each person independently. These assumptions fail in real-world, a…
Instance SegmentationHuman Mesh RecoveryUncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers
Visual affordances identify regions in an image with potential interactions, offering a novel paradigm for scene understanding. Recognizing affordances allows autonomous robots to act more naturally, could enhance human-…
Instance SegmentationScene UnderstandingNucEval: A Robust Evaluation Framework for Nuclear Instance Segmentation
In computational pathology, nuclear instance segmentation is a fundamental task with many downstream clinical applications. With the advent of deep learning, many approaches, including convolutional neural networks (CNNs…
Instance SegmentationMiniVLA-Nav v1: A Multi-Scene Simulation Dataset for Language-Conditioned Robot Navigation
We present MiniVLA-Nav v1, a simulation dataset for Language-Conditioned Object Approach (LCOA) navigation: given a short natural-language instruction, an NVIDIA Nova Carter differential-drive robot must navigate to the …
Instance SegmentationRobot NavigationWildLIFT: Lifting monocular drone video to 3D for species-agnostic wildlife monitoring
Monocular RGB cameras mounted on drones are widely used for wildlife monitoring, yet most analytical pipelines remain confined to two-dimensional image space, leaving geometric information in video underexploited. We pre…
Instance SegmentationPLAS-Net: Pixel-Level Area Segmentation for UAV-Based Beach Litter Monitoring
Accurate quantification of the physical exposure area of beach litter, rather than simple item counts, is essential for credible ecological risk assessment of marine debris. However, automated UAV-based monitoring predom…
Instance SegmentationBridging Foundation Models and ASTM Metallurgical Standards for Automated Grain Size Estimation from Microscopy Images
Extracting standardized metallurgical metrics from microscopy images remains challenging due to complex grain morphology and the data demands of supervised segmentation. To bridge foundational computer vision with practi…
Instance SegmentationSpatial Reasoning