Papers Object Proposal Generation
“Object Proposal Generation” 태그가 달린 논문 55편 · 필터 해제
PropVG: End-to-End Proposal-Driven Visual Grounding with Multi-Granularity Discrimination
Recent advances in visual grounding have largely shifted away from traditional proposal-based two-stage frameworks due to their inefficiency and high computational complexity, favoring end-to-end direct reference paradig…
Object Proposal GenerationContrastive LearningVisual GroundingAdapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation
Novel Instance Detection and Segmentation (NIDS) aims at detecting and segmenting novel object instances given a few examples of each instance. We propose a unified, simple, yet effective framework (NIDS-Net) comprising …
Instance SegmentationObject Proposal GenerationSemantic SegmentationTowards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic Grounding
Object proposal generation serves as a standard pre-processing step in Vision-Language (VL) tasks (image captioning, visual question answering, etc.). The performance of object proposals generated for VL tasks is current…
Graph GenerationImage CaptioningObjectObject Proposal Generation+3Small, but important: Traffic light proposals for detecting small traffic lights and beyond
Traffic light detection is a challenging problem in the context of self-driving cars and driver assistance systems. While most existing systems produce good results on large traffic lights, detecting small and tiny ones …
Object Proposal GenerationSelf-Driving CarsFast Segment Anything
The recently proposed segment anything model (SAM) has made a significant influence in many computer vision tasks. It is becoming a foundation step for many high-level tasks, like image segmentation, image caption, and i…
Edge DetectionImage SegmentationInstance SegmentationObject Proposal Generation+4SalienDet: A Saliency-based Feature Enhancement Algorithm for Object Detection for Autonomous Driving
Object detection (OD) is crucial to autonomous driving. On the other hand, unknown objects, which have not been seen in training sample set, are one of the reasons that hinder autonomous vehicles from driving beyond the …
Autonomous DrivingAutonomous VehiclesIncremental LearningObject+34D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation
In this work, we present a new paradigm, called 4D-StOP, to tackle the task of 4D Panoptic LiDAR Segmentation. 4D-StOP first generates spatio-temporal proposals using voting-based center predictions, where each point in …
4D Panoptic SegmentationObject Proposal GenerationPanoptic SegmentationSegmenting Medical Instruments in Minimally Invasive Surgeries using AttentionMask
Precisely locating and segmenting medical instruments in images of minimally invasive surgeries, medical instrument segmentation, is an essential first step for several tasks in medical image processing. However, image d…
ObjectObject Proposal GenerationSegmentationLocalizing Small Apples in Complex Apple Orchard Environments
The localization of fruits is an essential first step in automated agricultural pipelines for yield estimation or fruit picking. One example of this is the localization of apples in images of entire apple trees. Since th…
ObjectObject Proposal GenerationProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues
Object proposal generation is an important and fundamental task in computer vision. In this paper, we propose ProposalCLIP, a method towards unsupervised open-category object proposal generation. Unlike previous works wh…
Objectobject-detectionObject DetectionObject Proposal Generation+1Class-agnostic Object Detection with Multi-modal Transformer
What constitutes an object? This has been a long-standing question in computer vision. Towards this goal, numerous learning-free and learning-based approaches have been developed to score objectness. However, they genera…
Class-agnostic Object DetectionObjectobject-detectionObject Detection+2DeepFH Segmentations for Superpixel-based Object Proposal Refinement
Class-agnostic object proposal generation is an important first step in many object detection pipelines. However, object proposals of modern systems are rather inaccurate in terms of segmentation and only roughly adhere …
Objectobject-detectionObject DetectionObject Proposal Generation+2Superpixel-based Refinement for Object Proposal Generation
Precise segmentation of objects is an important problem in tasks like class-agnostic object proposal generation or instance segmentation. Deep learning-based systems usually generate segmentations of objects based on coa…
Instance SegmentationObjectObject Proposal GenerationSegmentation+13DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds
Visual grounding on 3D point clouds is an emerging vision and language task that benefits various applications in understanding the 3D visual world. By formulating this task as a grounding-by-detection problem, lots …
ObjectObject Proposal GenerationRelationVisual GroundingYou Don't Only Look Once: Constructing Spatial-Temporal Memory for Integrated 3D Object Detection and Tracking
Humans are able to continuously detect and track surrounding objects by constructing a spatial-temporal memory of the objects when looking around. In contrast, 3D object detectors in existing tracking-by-detection sy…
3D Object DetectionObjectobject-detectionObject Detection+23D Object Detection with Pointformer
Feature learning for 3D object detection from point clouds is very challenging due to the irregularity of 3D point cloud data. In this paper, we propose Pointformer, a Transformer backbone designed for 3D point clouds to…
3D Object DetectionObjectobject-detectionObject Detection+1UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection
Weakly supervised object detection (WSOD) has attracted extensive research attention due to its great flexibility of exploiting large-scale dataset with only image-level annotations for detector training. Despite its gre…
Objectobject-detectionObject DetectionObject Proposal Generation+1Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection
Point cloud semantic segmentation plays an essential role in autonomous driving, providing vital information about drivable surfaces and nearby objects that can aid higher level tasks such as path planning and collision …
3D Object Detection3D Semantic SegmentationAutonomous DrivingCollision Avoidance+5What leads to generalization of object proposals?
Object proposal generation is often the first step in many detection models. It is lucrative to train a good proposal model, that generalizes to unseen classes. This could help scaling detection models to larger number o…
DiversityObjectObject Proposal GenerationReal-time 3D object proposal generation and classification under limited processing resources
The task of detecting 3D objects is important to various robotic applications. The existing deep learning-based detection techniques have achieved impressive performance. However, these techniques are limited to run with…
3D Object DetectionClassificationGeneral ClassificationGPU+4