Object Proposal Generation

15 papers with code • 4 benchmarks • 5 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

CASENet: Deep Category-Aware Semantic Edge Detection

Lavender105/DFF CVPR 2017

To this end, we propose a novel end-to-end deep semantic edge learning architecture based on ResNet and a new skip-layer architecture where category-wise edge activations at the top convolution layer share and are fused with the same set of bottom layer features.

PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud

sshaoshuai/PointRCNN CVPR 2019

In this paper, we propose PointRCNN for 3D object detection from raw point cloud.

Multi-View 3D Object Detection Network for Autonomous Driving

bostondiditeam/MV3D CVPR 2017

We encode the sparse 3D point cloud with a compact multi-view representation.

Recurrent Pixel Embedding for Instance Grouping

aimerykong/Recurrent-Pixel-Embedding-for-Instance-Grouping CVPR 2018

We introduce a differentiable, end-to-end trainable framework for solving pixel-level grouping problems such as instance segmentation consisting of two novel components.

Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation

jponttuset/mcg 3 Mar 2015

We propose a unified approach for bottom-up hierarchical image segmentation and object proposal generation for recognition, called Multiscale Combinatorial Grouping (MCG).

Convolutional Channel Features

byangderek/CCF ICCV 2015

With the combination of CNN features and boosting forest, CCF benefits from the richer capacity in feature representation compared with channel features, as well as lower cost in computation and storage compared with end-to-end CNN methods.

Seq-NMS for Video Object Detection

tmoopenn/seq-nms 26 Feb 2016

Video object detection is challenging because objects that are easily detected in one frame may be difficult to detect in another frame within the same clip.

Semantic Instance Segmentation via Deep Metric Learning

alicranck/instance-seg 30 Mar 2017

We propose a new method for semantic instance segmentation, by first computing how likely two pixels are to belong to the same object, and then by grouping similar pixels together.

Object proposal generation applying the distance dependent Chinese restaurant process

laurimi/ddcrp-gibbs 12 Apr 2017

In application domains such as robotics, it is useful to represent the uncertainty related to the robot's belief about the state of its environment.

Semantic Edge Detection with Diverse Deep Supervision

arsenal9971/shearlet_semantic_edge 9 Apr 2018

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.