Papers Instance Segmentation
“Instance Segmentation” 태그가 달린 논문 2,537편 · 필터 해제
Neural Network Optimization Reimagined: Decoupled Techniques for Scratch and Fine-Tuning
With the accumulation of resources in the era of big data and the rise of pre-trained models in deep learning, optimizing neural networks for various tasks often involves different strategies for fine-tuning pre-trained …
Semantic SegmentationInstance SegmentationImage ClassificationObject DetectionPlankFormer: Robust Plankton Instance Segmentation via MAE-Pretrained Vision Transformers and Pseudo Community Image Generation
Plankton monitoring is essential for assessing aquatic ecosystems but is limited by the labor-intensive nature of manual microscopic analysis. Automating the segmentation of plankton from crowded images is crucial, howev…
Instance SegmentationImage GenerationPrompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery
Synthetic Aperture Radar (SAR) plays a critical role in maritime surveillance, yet deep learning for SAR analysis is limited by the lack of pixel-level annotations. This paper explores how general-purpose vision foundati…
Instance SegmentationAdvancing Vision Transformer with Enhanced Spatial Priors
In recent years, the Vision Transformer (ViT) has garnered significant attention within the computer vision community. However, the core component of ViT, Self-Attention, lacks explicit spatial priors and suffers from qu…
Semantic SegmentationInstance SegmentationImage ClassificationObject DetectionData Synthesis Improves 3D Myotube Instance Segmentation
Myotubes are multinucleated muscle fibers serving as key model systems for studying muscle physiology, disease mechanisms, and drug responses. Mechanistic studies and drug screening thereby rely on quantitative morpholog…
Instance SegmentationDomain AdaptationGranularity-Aware Transfer for Tree Instance Segmentation in Synthetic and Real Forests
We address the challenge of synthetic-to-real transfer in forestry perception where real data have only coarse Tree labels while synthetic data provide fine-grained trunk/crown annotations. We introduce MGTD, a mixed-gra…
Instance SegmentationCell Instance Segmentation via Multi-Task Image-to-Image Schrödinger Bridge
Existing cell instance segmentation pipelines typically combine deterministic predictions with post-processing, which imposes limited explicit constraints on the global structure of instance masks. In this work, we propo…
Instance SegmentationImage GenerationFRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation
The exponential growth of data from modern radio telescopes presents a significant challenge to traditional single-pulse search algorithms, which are computationally intensive and prone to high false-positive rates due t…
Instance SegmentationSelf-supervised Pretraining of Cell Segmentation Models
Instance segmentation enables the analysis of spatial and temporal properties of cells in microscopy images by identifying the pixels belonging to each cell. However, progress is constrained by the scarcity of high-quali…
Instance SegmentationCell SegmentationDiagnosing Urban Street Vitality via a Visual-Semantic and Spatiotemporal Framework for Street-Level Economics
Micro-scale street-level economic assessment is fundamental for precision spatial resource allocation. While Street View Imagery (SVI) advances urban sensing, existing approaches remain semantically superficial and overl…
Instance SegmentationMulti-task Just Recognizable Difference for Video Coding for Machines: Database, Model, and Coding Application
Just Recognizable Difference (JRD) boosts coding efficiency for machine vision through visibility threshold modeling, but is currently limited to a single-task scenario. To address this issue, we propose a Multi-Task JRD…
Instance SegmentationKeypoint DetectionObject DetectionCI-ICM: Channel Importance-driven Learned Image Coding for Machines
Traditional human vision-centric image compression methods are suboptimal for machine vision centric compression due to different visual properties and feature characteristics. To address this problem, we propose a Chann…
Instance SegmentationImage CompressionObject DetectionTraining a Student Expert via Semi-Supervised Foundation Model Distillation
Foundation models deliver strong perception but are often too computationally heavy to deploy, and adapting them typically requires costly annotations. We introduce a semi-supervised knowledge distillation (SSKD) framewo…
Knowledge DistillationInstance SegmentationDomain AdaptationDirector: Instance-aware Gaussian Splatting for Dynamic Scene Modeling and Understanding
Volumetric video seeks to model dynamic scenes as temporally coherent 4D representations. While recent Gaussian-based approaches achieve impressive rendering fidelity, they primarily emphasize appearance but are largely …
Instance SegmentationScene UnderstandingDense Point-to-Mask Optimization with Reinforced Point Selection for Crowd Instance Segmentation
Crowd instance segmentation is a crucial task with a wide range of applications, including surveillance and transportation. Currently, point labels are common in crowd datasets, while region labels (e.g., boxes) are rare…
Instance SegmentationLifting Unlabeled Internet-level Data for 3D Scene Understanding
Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this paper, we demonstrate that carefully designed data engines can leverage web-curat…
Visual Question AnsweringInstance Segmentation3D Object DetectionScene UnderstandingIndoorCrowd: A Multi-Scene Dataset for Human Detection, Segmentation, and Tracking with an Automated Annotation Pipeline
Understanding human behaviour in crowded indoor environments is central to surveillance, smart buildings, and human-robot interaction, yet existing datasets rarely capture real-world indoor complexity at scale. We introd…
Multi-Object TrackingInstance SegmentationLightweight Spatiotemporal Highway Lane Detection via 3D-ResNet and PINet with ROI-Aware Attention
This paper presents a lightweight, end-to-end highway lane detection architecture that jointly captures spatial and temporal information for robust performance in real-world driving scenarios. Building on the strengths o…
Instance SegmentationLane DetectionProgressive Prompt-Guided Cross-Modal Reasoning for Referring Image Segmentation
Referring image segmentation aims to localize and segment a target object in an image based on a free-form referring expression. The core challenge lies in effectively bridging linguistic descriptions with object-level v…
Semantic SegmentationInstance SegmentationReferring ExpressionImage SegmentationAdapting SAM to Nuclei Instance Segmentation and Classification via Cooperative Fine-Grained Refinement
Nuclei instance segmentation is critical in computational pathology for cancer diagnosis and prognosis. Recently, the Segment Anything Model has demonstrated exceptional performance in various segmentation tasks, leverag…
parameter-efficient fine-tuningInstance Segmentation