Object Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 18
- 보존된 평가 기록
- 51
Object Localization is the task of locating an instance of a particular object category in an image, typically by specifying a tightly cropped bounding box centered on the instance. An object proposal specifies a candidate bounding box, and an object proposal is said to be a correct localization if it sufficiently overlaps a human-labeled “ground-truth” bounding box for the given object. In the literature, the “Object Localization” task is to locate one instance of an object category, whereas “object detection” focuses on locating all instances of a category in a given image.
Source: Fast On-Line Kernel Density Estimation for Active Object Localization
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Mask-aware Text-to-Image Retrieval: Referring Expression Segmentation Meets Cross-modal Retrieval
RAG-6DPose: Retrieval-Augmented 6D Pose Estimation via Leveraging CAD as Knowledge Base
CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusion
UAV Object Detection and Positioning in a Mining Industrial Metaverse with Custom Geo-Referenced Data
WoMAP: World Models For Embodied Open-Vocabulary Object Localization
Multispectral Detection Transformer with Infrared-Centric Sensor Fusion
Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels
Towards Omnidirectional Reasoning with 360-R1: A Dataset, Benchmark, and GRPO-based Method
PointArena: Probing Multimodal Grounding Through Language-Guided Pointing
Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous Driving
Towards Accurate State Estimation: Kalman Filter Incorporating Motion Dynamics for 3D Multi-Object Tracking
Pro2SAM: Mask Prompt to SAM with Grid Points for Weakly Supervised Object Localization
Split Matching for Inductive Zero-shot Semantic Segmentation
Enhancing Satellite Object Localization with Dilated Convolutions and Attention-aided Spatial Pooling
Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfer
Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation
CFIS-YOLO: A Lightweight Multi-Scale Fusion Network for Edge-Deployable Wood Defect Detection
Multi-Object Grounding via Hierarchical Contrastive Siamese Transformers
SoccerNet-v3D: Leveraging Sports Broadcast Replays for 3D Scene Understanding
Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization
POEM: Precise Object-level Editing via MLLM control
Texture or Semantics? Vision-Language Models Get Lost in Font Recognition
PixelCAM: Pixel Class Activation Mapping for Histology Image Classification and ROI Localization
MB-ORES: A Multi-Branch Object Reasoner for Visual Grounding in Remote Sensing
Multiview Image-Based Localization
GLRD: Global-Local Collaborative Reason and Debate with PSL for 3D Open-Vocabulary Detection
Beyond Object Categories: Multi-Attribute Reference Understanding for Visual Grounding
xMOD: Cross-Modal Distillation for 2D/3D Multi-Object Discovery from 2D motion
Omnidirectional Multi-Object Tracking
Dr. Splat: Directly Referring 3D Gaussian Splatting via Direct Language Embedding Registration
CrossOver: 3D Scene Cross-Modal Alignment
Qwen2.5-VL Technical Report
MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval
Auto-Prompting SAM for Weakly Supervised Landslide Extraction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.