Scene Segmentation

25 papers with code · Computer Vision

Scene segmentation is the task of splitting a scene into its various object components.

Image adapted from Temporally coherent 4D reconstruction of complex dynamic scenes.

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Greatest papers with code

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

22 Dec 2014tensorflow/models

This is due to the very invariance properties that make DCNNs good for high level tasks.

REAL-TIME SEMANTIC SEGMENTATION SCENE SEGMENTATION

Fully Convolutional Networks for Semantic Segmentation

CVPR 2015 pytorch/vision

Convolutional networks are powerful visual models that yield hierarchies of features.

REAL-TIME SEMANTIC SEGMENTATION SCENE SEGMENTATION

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

2 Nov 2015divamgupta/image-segmentation-keras

We show that SegNet provides good performance with competitive inference time and more efficient inference memory-wise as compared to other architectures.

CROWD COUNTING LESION SEGMENTATION REAL-TIME SEMANTIC SEGMENTATION SCENE SEGMENTATION SCENE UNDERSTANDING

Dual Attention Network for Scene Segmentation

CVPR 2019 junfu1115/DANet

Specifically, we append two types of attention modules on top of traditional dilated FCN, which model the semantic interdependencies in spatial and channel dimensions respectively.

SCENE SEGMENTATION

Point-Voxel CNN for Efficient 3D Deep Learning

NeurIPS 2019 mit-han-lab/pvcnn

The computation cost and memory footprints of the voxel-based models grow cubically with the input resolution, making it memory-prohibitive to scale up the resolution.

 SOTA for 3D Instance Segmentation on S3DIS (mAcc metric )

3D OBJECT DETECTION SCENE SEGMENTATION

Seamless Scene Segmentation

CVPR 2019 mapillary/seamseg

In this work we introduce a novel, CNN-based architecture that can be trained end-to-end to deliver seamless scene segmentation results.

PANOPTIC SEGMENTATION SCENE SEGMENTATION

SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

CVPR 2018 laughtervv/SGPN

Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results.

3D INSTANCE SEGMENTATION 3D OBJECT DETECTION 3D SEMANTIC INSTANCE SEGMENTATION SCENE SEGMENTATION

End-to-end Learning of Driving Models from Large-scale Video Datasets

CVPR 2017 gy20073/BDD_Driving_Model

Robust perception-action models should be learned from training data with diverse visual appearances and realistic behaviors, yet current approaches to deep visuomotor policy learning have been generally limited to in-situ models learned from a single vehicle or a simulation environment.

SCENE SEGMENTATION