Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning
3D dense captioning requires a model to translate its understanding of an input 3D scene into several captions associated with different object regions. Existing methods adopt a sophisticated "detect-then-describe" pipel…
3D dense captioningCaption GenerationDense CaptioningObject+2Semantic-Constraint Matching Transformer for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) strives to learn to localize objects with only image-level supervision. Due to the local receptive fields generated by convolution operations, previous CNN-based methods suffe…
ObjectObject LocalizationWeakly-Supervised Object LocalizationObject-Centric Multiple Object Tracking
Unsupervised object-centric learning methods allow the partitioning of scenes into entities without additional localization information and are excellent candidates for reducing the annotation burden of multiple-object t…
Multiple Object TrackingObjectobject-detectionObject Detection+2Referring Image Segmentation Using Text Supervision
Existing Referring Image Segmentation (RIS) methods typically require expensive pixel-level or box-level annotations for supervision. In this paper, we observe that the referring texts used in RIS already provide suffici…
Image SegmentationObject LocalizationReferring Expression SegmentationSegmentation+2I3DOD: Towards Incremental 3D Object Detection via Prompting
3D object detection has achieved significant performance in many fields, e.g., robotics system, autonomous driving, and augmented reality. However, most existing methods could cause catastrophic forgetting of old classes…
3D Object DetectionAutonomous DrivingObjectobject-detection+2Video OWL-ViT: Temporally-consistent open-world localization in video
We present an architecture and a training recipe that adapts pre-trained open-world image models to localization in videos. Understanding the open visual world (without being constrained by fixed label spaces) is crucial…
DecoderObjectObject LocalizationTowards Grounded Visual Spatial Reasoning in Multi-Modal Vision Language Models
Large vision-and-language models (VLMs) trained to match images with text on large-scale datasets of image-text pairs have shown impressive generalization ability on several vision and language tasks. Several recent work…
Image-text matchingObject LocalizationQuestion AnsweringSpatial Reasoning+3Leveraging Next-Active Objects for Context-Aware Anticipation in Egocentric Videos
Objects are crucial for understanding human-object interactions. By identifying the relevant objects, one can also predict potential future interactions or actions that may occur with these objects. In this paper, we stu…
Action AnticipationActive Object LocalizationHuman-Object Interaction DetectionObject+2Rethinking the Localization in Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) is one of the most popular and challenging tasks in computer vision. This task is to localize the objects in the images given only the image-level supervision. Recently, divid…
ObjectObject LocalizationWeakly-Supervised Object LocalizationRapid Training Data Creation by Synthesizing Medical Images for Classification and Localization
While the use of artificial intelligence (AI) for medical image analysis is gaining wide acceptance, the expertise, time and cost required to generate annotated data in the medical field are significantly high, due to li…
Medical Image AnalysisObject LocalizationAll-pairs Consistency Learning for Weakly Supervised Semantic Segmentation
In this work, we propose a new transformer-based regularization to better localize objects for Weakly supervised semantic segmentation (WSSS). In image-level WSSS, Class Activation Map (CAM) is adopted to generate object…
AllObject LocalizationSemantic SegmentationWeakly supervised Semantic Segmentation+1MCTformer+: Multi-Class Token Transformer for Weakly Supervised Semantic Segmentation
This paper proposes a novel transformer-based framework that aims to enhance weakly supervised semantic segmentation (WSSS) by generating accurate class-specific object localization maps as pseudo labels. Building upon t…
Object LocalizationSemantic SegmentationWeakly supervised Semantic SegmentationWeakly-Supervised Semantic SegmentationA Memory-Augmented Multi-Task Collaborative Framework for Unsupervised Traffic Accident Detection in Driving Videos
Identifying traffic accidents in driving videos is crucial to ensuring the safety of autonomous driving and driver assistance systems. To address the potential danger caused by the long-tailed distribution of driving eve…
Autonomous DrivingObjectObject LocalizationOptical Flow Estimation+1Optical Flow boosts Unsupervised Localization and Segmentation
Unsupervised localization and segmentation are long-standing robot vision challenges that describe the critical ability for an autonomous robot to learn to decompose images into individual objects without labeled data. T…
Lifelong learningObjectObject LocalizationOptical Flow Estimation+4Cascade-DETR: Delving into High-Quality Universal Object Detection
Object localization in general environments is a fundamental part of vision systems. While dominating on the COCO benchmark, recent Transformer-based detection methods are not competitive in diverse domains. Moreover, th…
DecoderObjectobject-detectionObject Detection+1Generative Prompt Model for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) remains challenging when learning object localization models from image category labels. Conventional methods that discriminatively train activation models ignore representati…
DenoisingImage DenoisingLanguage ModelingLanguage Modelling+4MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression
Bounding box regression (BBR) has been widely used in object detection and instance segmentation, which is an important step in object localization. However, most of the existing loss functions for bounding box regressio…
Instance SegmentationObjectobject-detectionObject Detection+4YOLIC: An Efficient Method for Object Localization and Classification on Edge Devices
In the realm of Tiny AI, we introduce ``You Only Look at Interested Cells" (YOLIC), an efficient method for object localization and classification on edge devices. Through seamlessly blending the strengths of semantic se…
ClassificationComputational EfficiencyCPUMulti-Label Classification+6Open-Vocabulary Object Detection via Scene Graph Discovery
In recent years, open-vocabulary (OV) object detection has attracted increasing research attention. Unlike traditional detection, which only recognizes fixed-category objects, OV detection aims to detect objects in an op…
DecoderGraph GenerationObjectobject-detection+6EgoCOL: Egocentric Camera pose estimation for Open-world 3D object Localization @Ego4D challenge 2023
We present EgoCOL, an egocentric camera pose estimation method for open-world 3D object localization. Our method leverages sparse camera pose reconstructions in a two-fold manner, video and scan independently, to estimat…
Camera Pose EstimationObjectObject LocalizationPose Estimation