Learning Rich Features from RGB-D Images for Object Detection and Segmentation

Random Forests

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Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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Object Detection with Discriminatively Trained Part-Based Models

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Contour Detection and Hierarchical Image Segmentation

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DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

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Learning Hierarchical Features for Scene Labeling

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Real-time human pose recognition in parts from single depth images

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A large-scale hierarchical multi-view RGB-D object dataset

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Simultaneous Detection and Segmentation

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Multiscale Combinatorial Grouping

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Fast Edge Detection Using Structured Forests

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Structured Forests for Fast Edge Detection

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Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images

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Convolutional-Recursive Deep Learning for 3D Object Classification

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Indoor Semantic Segmentation using depth information

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Sketch Tokens: A Learned Mid-level Representation for Contour and Object Detection

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RGB-(D) scene labeling: Features and algorithms

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Unsupervised Feature Learning for RGB-D Based Object Recognition

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Semantic Labeling of 3D Point Clouds for Indoor Scenes

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A Category-Level 3D Object Dataset: Putting the Kinect to Work

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Holistic Scene Understanding for 3D Object Detection with RGBD Cameras

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Discriminatively Trained Sparse Code Gradients for Contour Detection

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Histogram of Oriented Normal Vectors for Object Recognition with a Depth Sensor

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Scene Parsing with Object Instances and Occlusion Ordering

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Support Surface Prediction in Indoor Scenes

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Accurate Localization of 3D Objects from RGB-D Data Using Segmentation Hypotheses

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Building Part-Based Object Detectors via 3D Geometry

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Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning

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CPMC-3D-O2P: Semantic segmentation of RGB-D images using CPMC and Second Order Pooling.

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Fully convolutional networks for semantic segmentation

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Fully convolutional networks for semantic segmentation

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Deep convolutional neural networks for computer-aided detection: cnn architectures, dataset characteristics and transfer learning

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Adversarial Discriminative Domain Adaptation

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RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

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Region-based convolutional networks for accurate object detection and segmentation

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Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture

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SUN RGB-D: A RGB-D scene understanding benchmark suite

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Matterport3D: Learning from RGB-D Data in Indoor Environments

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Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

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FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture

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Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

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Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

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ImageBind One Embedding Space to Bind Them All

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Holistically-nested edge detection

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CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation With Transformers

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MFNet: Towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes

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A review of object detection based on deep learning

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Vehicle Detection from 3D Lidar Using Fully Convolutional Network

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Cross Modal Distillation for Supervision Transfer

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3D Graph Neural Networks for RGBD Semantic Segmentation

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UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders

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Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation

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KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving

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Feature Transfer Learning for Face Recognition With Under-Represented Data

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Deep multimodal fusion for semantic image segmentation: A survey

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Disparity-Based Multiscale Fusion Network for Transportation Detection

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FuseSeg: LiDAR Point Cloud Segmentation Fusing Multi-Modal Data

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Traffic Scene Segmentation Based on RGB-D Image and Deep Learning

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Exploring RGB+Depth Fusion for Real-Time Object Detection

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Depth-Adaptive Deep Neural Network for Semantic Segmentation

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Multiscale fully convolutional network with application to industrial inspection

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Learning Deep Multimodal Feature Representation with Asymmetric Multi-layer Fusion

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3D-SSD: Learning hierarchical features from RGB-D images for amodal 3D object detection

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Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation

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Multimodal semantic segmentation in autonomous driving: A review of current approaches and future perspectives

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Multi-Modal Sensor Fusion-Based Semantic Segmentation for Snow Driving Scenarios

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Decoupling Common and Unique Representations for Multimodal Self-supervised Learning

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Complete 3D Scene Parsing from an RGBD Image

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Rock Segmentation in the Navigation Vision of the Planetary Rovers

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Progressive modality cooperation for multi-modality domain adaptation

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Outdoor RGBD Instance Segmentation With Residual Regretting Learning

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Multi-level progressive parallel attention guided salient object detection for RGB-D images

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A central multimodal fusion framework for outdoor scene image segmentation

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