Object Proposal Generation
20 papers with code • 4 benchmarks • 4 datasets
Object proposal generation is a preprocessing technique that has been widely used in current object detection pipelines to guide the search of objects and avoid exhaustive sliding window search across images.
( Image credit: Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation )
Most implemented papers
Semantic Edge Detection with Diverse Deep Supervision
Semantic edge detection (SED), which aims at jointly extracting edges as well as their category information, has far-reaching applications in domains such as semantic segmentation, object proposal generation, and object recognition.
AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects
We propose a novel approach for class-agnostic object proposal generation, which is efficient and especially well-suited to detect small objects.
UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection
In this paper, we propose a unified WSOD framework, termed UWSOD, to develop a high-capacity general detection model with only image-level labels, which is self-contained and does not require external modules or additional supervision.
3D Object Detection with Pointformer
In this paper, we propose Pointformer, a Transformer backbone designed for 3D point clouds to learn features effectively.
Superpixel-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.
Class-agnostic Object Detection with Multi-modal Transformer
This has been a long-standing question in computer vision.
4D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation
Our voting-based tracklet generation method followed by geometric feature-based aggregation generates significantly improved panoptic LiDAR segmentation quality when compared to modeling the entire 4D volume using Gaussian probability distributions.
SalienDet: A Saliency-based Feature Enhancement Algorithm for Object Detection for 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 operational domain.
Fast Segment Anything
In this paper, we propose a speed-up alternative method for this fundamental task with comparable performance.
Towards 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.).