Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
Explaining Multi-modal Large Language Models by Analyzing their Vision Perception
Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in understanding and generating content across various modalities, such as images and text. However, their interpretability remains a ch…
Object LocalizationConcept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNet
Advances in multi-modal embeddings, and in particular CLIP, have recently driven several breakthroughs in Computer Vision (CV). CLIP has shown impressive performance on a variety of tasks, yet, its inherently opaque arch…
Object LocalizationOut-of-Distribution DetectionMany-Shot In-Context Learning in Multimodal Foundation Models
Large language models are effective at few-shot in-context learning (ICL). Recent advancements in multimodal foundation models have enabled unprecedentedly long context windows, presenting an opportunity to explore their…
image-classificationImage ClassificationIn-Context LearningObject LocalizationMasked Multi-Query Slot Attention for Unsupervised Object Discovery
Unsupervised object discovery is becoming an essential line of research for tackling recognition problems that require decomposing an image into entities, such as semantic segmentation and object detection. Recently, obj…
Objectobject-detectionObject DetectionObject Discovery+2Source-Free Domain Adaptation of Weakly-Supervised Object Localization Models for Histology
Given the emergence of deep learning, digital pathology has gained popularity for cancer diagnosis based on histology images. Deep weakly supervised object localization (WSOL) models can be trained to classify histology …
Contrastive LearningDomain AdaptationObject LocalizationSource-Free Domain Adaptation+2Mamba-FETrack: Frame-Event Tracking via State Space Model
RGB-Event based tracking is an emerging research topic, focusing on how to effectively integrate heterogeneous multi-modal data (synchronized exposure video frames and asynchronous pulse Event stream). Existing works typ…
GPUMambaObject LocalizationEquivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection
Popular representation learning methods encourage feature invariance under transformations applied at the input. However, in 3D perception tasks like object localization and segmentation, outputs are naturally equivarian…
3D Object DetectionObjectobject-detectionObject Detection+2Improving Weakly-Supervised Object Localization Using Adversarial Erasing and Pseudo Label
Weakly-supervised learning approaches have gained significant attention due to their ability to reduce the effort required for human annotations in training neural networks. This paper investigates a framework for weakly…
ObjectObject LocalizationPseudo LabelWeakly-supervised Learning+1Real-world Instance-specific Image Goal Navigation: Bridging Domain Gaps via Contrastive Learning
Improving instance-specific image goal navigation (InstanceImageNav), which locates the identical object in a real-world environment from a query image, is essential for robotic systems to assist users in finding desired…
Contrastive LearningDeblurringImage EnhancementObject LocalizationA Realistic Protocol for Evaluation of Weakly Supervised Object Localization
Weakly Supervised Object Localization (WSOL) allows training deep learning models for classification and localization (LOC) using only global class-level labels. The absence of bounding box (bbox) supervision during trai…
Model SelectionObjectObject LocalizationRegion Proposal+1IDD-X: A Multi-View Dataset for Ego-relative Important Object Localization and Explanation in Dense and Unstructured Traffic
Intelligent vehicle systems require a deep understanding of the interplay between road conditions, surrounding entities, and the ego vehicle's driving behavior for safe and efficient navigation. This is particularly crit…
ObjectObject LocalizationO2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation
Online construction of open-ended language scenes is crucial for robotic applications, where open-vocabulary interactive scene understanding is required. Recently, neural implicit representation has provided a promising …
Image SegmentationObjectObject LocalizationScene Understanding+2MOSE: Boosting Vision-based Roadside 3D Object Detection with Scene Cues
3D object detection based on roadside cameras is an additional way for autonomous driving to alleviate the challenges of occlusion and short perception range from vehicle cameras. Previous methods for roadside 3D object …
3D Object DetectionAutonomous DrivingDecoderMonocular 3D Object Detection+4FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery
Object detection in remotely sensed satellite pictures is fundamental in many fields such as biophysical, and environmental monitoring. While deep learning algorithms are constantly evolving, they have been mostly implem…
Objectobject-detectionObject DetectionObject Detection In Aerial Images+3Towards Two-Stream Foveation-based Active Vision Learning
Deep neural network (DNN) based machine perception frameworks process the entire input in a one-shot manner to provide answers to both "what object is being observed" and "where it is located". In contrast, the "two-stre…
FoveationObjectObject LocalizationWeakly-Supervised Object LocalizationIllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models
The advent of Vision Language Models (VLM) has allowed researchers to investigate the visual understanding of a neural network using natural language. Beyond object classification and detection, VLMs are capable of visua…
Common Sense ReasoningIn-Context LearningMultiple-choiceObject Localization+2Spatio-Temporal Bi-directional Cross-frame Memory for Distractor Filtering Point Cloud Single Object Tracking
3D single object tracking within LIDAR point clouds is a pivotal task in computer vision, with profound implications for autonomous driving and robotics. However, existing methods, which depend solely on appearance match…
3D Single Object TrackingAutonomous DrivingObject LocalizationObject TrackingPoint-DETR3D: Leveraging Imagery Data with Spatial Point Prior for Weakly Semi-supervised 3D Object Detection
Training high-accuracy 3D detectors necessitates massive labeled 3D annotations with 7 degree-of-freedom, which is laborious and time-consuming. Therefore, the form of point annotations is proposed to offer significant p…
3D Object Detectionobject-detectionObject DetectionObject Localization+1Semantic Gaussians: Open-Vocabulary Scene Understanding with 3D Gaussian Splatting
Open-vocabulary 3D scene understanding presents a significant challenge in computer vision, with wide-ranging applications in embodied agents and augmented reality systems. Existing methods adopt neurel rendering methods…
Instance SegmentationObject LocalizationScene UnderstandingSegmentation+2EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative sensing system that splits the task into…
ClassificationObjectobject-detectionObject Detection+1