Papers RGBD Semantic Segmentation
“RGBD Semantic Segmentation” 태그가 달린 논문 14편 · 필터 해제
Revisiting Cross-Modal Knowledge Distillation: A Disentanglement Approach for RGBD Semantic Segmentation
Multi-modal RGB and Depth (RGBD) data are predominant in many domains such as robotics, autonomous driving and remote sensing. The combination of these multi-modal data enhances environmental perception by providing 3D s…
Autonomous DrivingContrastive LearningData AugmentationDisentanglement+3HDBFormer: Efficient RGB-D Semantic Segmentation with A Heterogeneous Dual-Branch Framework
In RGB-D semantic segmentation for indoor scenes, a key challenge is effectively integrating the rich color information from RGB images with the spatial distance information from depth images. However, most existing meth…
RGBD Semantic SegmentationSemantic SegmentationDFormerv2: Geometry Self-Attention for RGBD Semantic Segmentation
Recent advances in scene understanding benefit a lot from depth maps because of the 3D geometry information, especially in complex conditions (e.g., low light and overexposed). Existing approaches encode depth maps along…
3D geometryRGBD Semantic SegmentationScene UnderstandingSemantic SegmentationCSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving Scenes
Semantic segmentation, as a crucial component of complex visual interpretation, plays a fundamental role in autonomous vehicle vision systems. Recent studies have significantly improved the accuracy of semantic segmentat…
Autonomous VehiclesImage SegmentationReal-Time Semantic SegmentationRGBD Semantic Segmentation+4FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything
In the realm of computer vision, the integration of advanced techniques into the processing of RGB-D camera inputs poses a significant challenge, given the inherent complexities arising from diverse environmental conditi…
3D Object ReconstructionInstance SegmentationObjectobject-detection+6Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning
Multimodal (e.g., RGB-Depth/RGB-Thermal) fusion has shown great potential for improving semantic segmentation in complex scenes (e.g., indoor/low-light conditions). Existing approaches often fully fine-tune a dual-branch…
Decoderobject-detectionObject DetectionPrompt Learning+6DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
We present DFormer, a novel RGB-D pretraining framework to learn transferable representations for RGB-D segmentation tasks. DFormer has two new key innovations: 1) Unlike previous works that encode RGB-D information with…
3D geometryDecoderobject-detectionObject Detection+6Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation
Using multiple spatial modalities has been proven helpful in improving semantic segmentation performance. However, there are several real-world challenges that have yet to be addressed: (a) improving label efficiency and…
RGBD Semantic SegmentationRobust Semi-Supervised RGBD Semantic SegmentationSegmentationSemantic Segmentation+2Attention-based Dual Supervised Decoder for RGBD Semantic Segmentation
Encoder-decoder models have been widely used in RGBD semantic segmentation, and most of them are designed via a two-stream network. In general, jointly reasoning the color and geometric information from RGBD is beneficia…
DecoderRGBD Semantic SegmentationSegmentationSemantic SegmentationSpatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation
3D spatial information is known to be beneficial to the semantic segmentation task. Most existing methods take 3D spatial data as an additional input, leading to a two-stream segmentation network that processes RGB and 3…
RGBD Semantic SegmentationSegmentationSemantic SegmentationScene Completeness-Aware Lidar Depth Completion for Driving Scenario
This paper introduces Scene Completeness-Aware Depth Completion (SCADC) to complete raw lidar scans into dense depth maps with fine and complete scene structures. Recent sparse depth completion for lidars only focuses on…
Depth CompletionRGBD Semantic SegmentationScene UnderstandingSemantic Segmentation+2ACNet: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation
Compared to RGB semantic segmentation, RGBD semantic segmentation can achieve better performance by taking depth information into consideration. However, it is still problematic for contemporary segmenters to effectively…
RGBD Semantic SegmentationSegmentationSemantic SegmentationThermal Image Segmentation3D Graph Neural Networks for RGBD Semantic Segmentation
RGBD semantic segmentation requires joint reasoning about 2D appearance and 3D geometric information. In this paper we propose a 3D graph neural network (3DGNN) that builds a k-nearest neighbor graph on top of 3D point c…
Graph Neural NetworkRGBD Semantic SegmentationSemantic SegmentationSTD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling
We propose a novel superpixel-based multi-view convolutional neural network for semantic image segmentation. The proposed network produces a high quality segmentation of a single image by leveraging information from addi…
Image SegmentationOptical Flow EstimationRGBD Semantic SegmentationSegmentation+2