Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
AIVD: Adaptive Edge-Cloud Collaboration for Accurate and Efficient Industrial Visual Detection
Multimodal large language models (MLLMs) demonstrate exceptional capabilities in semantic understanding and visual reasoning, yet they still face challenges in precise object localization and resource-constrained edge-cl…
Object LocalizationVisual ReasoningNoise-Robust Tiny Object Localization with Flows
Despite significant advances in generic object detection, a persistent performance gap remains for tiny objects compared to normal-scale objects. We demonstrate that tiny objects are highly sensitive to annotation noise,…
Object LocalizationObject DetectionMoniRefer: A Real-world Large-scale Multi-modal Dataset based on Roadside Infrastructure for 3D Visual Grounding
3D visual grounding aims to localize the object in 3D point cloud scenes that semantically corresponds to given natural language sentences. It is very critical for roadside infrastructure system to interpret natural lang…
Object LocalizationVisual GroundingGVSynergy-Det: Synergistic Gaussian-Voxel Representations for Multi-View 3D Object Detection
Image-based 3D object detection aims to identify and localize objects in 3D space using only RGB images, eliminating the need for expensive depth sensors required by point cloud-based methods. Existing image-based approa…
Representation LearningObject Localization3D Object DetectionPoint CloudsDeFloMat: Detection with Flow Matching for Stable and Efficient Generative Object Localization
We propose DeFloMat (Detection with Flow Matching), a novel generative object detection framework that addresses the critical latency bottleneck of diffusion-based detectors, such as DiffusionDet, by integrating Conditio…
Object LocalizationObject DetectionLong-Range depth estimation using learning based Hybrid Distortion Model for CCTV cameras
Accurate camera models are essential for photogrammetry applications such as 3D mapping and object localization, particularly for long distances. Various stereo-camera based 3D localization methods are available but are …
Object LocalizationDepth EstimationN3D-VLM: Native 3D Grounding Enables Accurate Spatial Reasoning in Vision-Language Models
While current multimodal models can answer questions based on 2D images, they lack intrinsic 3D object perception, limiting their ability to comprehend spatial relationships and depth cues in 3D scenes. In this work, we …
Object LocalizationSpatial ReasoningDepth EstimationVisual ReasoningAssisted Refinement Network Based on Channel Information Interaction for Camouflaged and Salient Object Detection
Camouflaged Object Detection (COD) stands as a significant challenge in computer vision, dedicated to identifying and segmenting objects visually highly integrated with their backgrounds. Current mainstream methods have …
Salient Object DetectionObject LocalizationPolyp SegmentationHybrid Transformer-Mamba for Weakly Supervised Volumetric Medical Segmentation
Weakly supervised segmentation enables model training from plane-level labels. Existing methods often rely on 2D encoders, neglecting the volumetric nature of medical data. We propose TranSamba, a hybrid Transformer-Mamb…
Object LocalizationZeBROD: Zero-Retraining Based Recognition and Object Detection Framework
Object detection constitutes the primary task within the domain of computer vision. It is utilized in numerous domains. Nonetheless, object detection continues to encounter the issue of catastrophic forgetting. The model…
Object LocalizationObject DetectionMetric LearningReDirector: Creating Any-Length Video Retakes with Rotary Camera Encoding
We present ReDirector, a novel camera-controlled video retake generation method for dynamically captured variable-length videos. In particular, we rectify a common misuse of RoPE in previous works by aligning the spatiot…
Object LocalizationLAA3D: A Benchmark of Detecting and Tracking Low-Altitude Aircraft in 3D Space
Perception of Low-Altitude Aircraft (LAA) in 3D space enables precise 3D object localization and behavior understanding. However, datasets tailored for 3D LAA perception remain scarce. To address this gap, we present LAA…
3D Multi-Object TrackingObject Localization3D Object DetectionPose EstimationO3SLM: Open Weight, Open Data, and Open Vocabulary Sketch-Language Model
While Large Vision Language Models (LVLMs) are increasingly deployed in real-world applications, their ability to interpret abstract visual inputs remains limited. Specifically, they struggle to comprehend hand-drawn ske…
Visual Question AnsweringObject LocalizationImage RetrievalLayerEdit: Disentangled Multi-Object Editing via Conflict-Aware Multi-Layer Learning
Text-driven multi-object image editing which aims to precisely modify multiple objects within an image based on text descriptions, has recently attracted considerable interest. Existing works primarily follow the localiz…
Object LocalizationImage EditingMono3DVG-EnSD: Enhanced Spatial-aware and Dimension-decoupled Text Encoding for Monocular 3D Visual Grounding
Monocular 3D Visual Grounding (Mono3DVG) is an emerging task that locates 3D objects in RGB images using text descriptions with geometric cues. However, existing methods face two key limitations. Firstly, they often over…
Object LocalizationVisual GroundingSpatialLock: Precise Spatial Control in Text-to-Image Synthesis
Text-to-Image (T2I) synthesis has made significant advancements in recent years, driving applications such as generating datasets automatically. However, precise control over object localization in generated images remai…
Object LocalizationMask-to-Height: A YOLOv11-Based Architecture for Joint Building Instance Segmentation and Height Classification from Satellite Imagery
Accurate building instance segmentation and height classification are critical for urban planning, 3D city modeling, and infrastructure monitoring. This paper presents a detailed analysis of YOLOv11, the recent advanceme…
Instance SegmentationObject LocalizationRegion-CAM: Towards Accurate Object Regions in Class Activation Maps for Weakly Supervised Learning Tasks
Class Activation Mapping (CAM) methods are widely applied in weakly supervised learning tasks due to their ability to highlight object regions. However, conventional CAM methods highlight only the most discriminative reg…
Semantic SegmentationObject LocalizationSeeing the Unseen: Mask-Driven Positional Encoding and Strip-Convolution Context Modeling for Cross-View Object Geo-Localization
Cross-view object geo-localization enables high-precision object localization through cross-view matching, with critical applications in autonomous driving, urban management, and disaster response. However, existing meth…
Object LocalizationAutonomous DrivingEnhancing Rotated Object Detection via Anisotropic Gaussian Bounding Box and Bhattacharyya Distance
Detecting rotated objects accurately and efficiently is a significant challenge in computer vision, particularly in applications such as aerial imagery, remote sensing, and autonomous driving. Although traditional object…
Object LocalizationAutonomous DrivingObject Detection