We evaluate our method on two popular RGBD datasets: NYUD2 and SUN-RGBD. NYUD2 contains a total of 1,449 RGBD image pairs from 464 different scenes. The dataset is divided into 795 images from 249 scenes for training and 654 images from 215 scenes for testing. We randomly split 49 sce...
针对你遇到的问题,即文件/root/autodl-tmp/rgbd_semantic_segmentation/models/net_utils.py不是UTF-8编码,以下是一些详细的解决步骤: 1. 确认文件的当前编码格式 要确认文件的当前编码格式,你可以使用file命令(在Linux或macOS系统上)来检查。不过,file命令可能不会直接显示文件的编码,但它可以给出一些线索。更可靠...
所提出的网络通过利用来自相同场景的(additional views)附加视图的信息来产生单个图像的高质量分割。特别是在室内视频中,例如由机器人平台或手持式和身体穿戴的RGBD相机拍摄的视频,(nearby video frames)相邻的视频帧提供了不同的视点、物体和场景的附加上下文(addititional context of objects and scenes)。为了利用这些...
Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis 摘要:摘要—全面分析场景对于在不同环境中行动的机器人至关重要。语义分割可以增强各种后续任务,例如(语义辅助)人的感知,(语义)自由空间检测,(语义)映射和(语义)导航。在本文中,我们提出了一种高效且强大的RGB-D分割方法,该方法可以使用NVIDIA TensorR...
RGBD_Semantic_Segmentation_PyTorch News Main Results Results on NYU Depth V2 Test Set with Multi-scale Inference Results on CityScapes Test Set with Multi-scale Inference (out method uses output stride=16 and does not use coarse-labeled data) ...
3D Graph Neural Networks for RGBD Semantic Segmentation Xiaojuan Qi† Renjie Liao‡,§ Jiaya Jia†,♭ Sanja Fidler‡ Raquel Urtasun§,‡ † The Chinese University of Hong Kong ‡ University of Toronto § Uber Advanced Technologies Group ♭ Youtu Lab, Tencent {xjqi, leojia}@cse....
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data- Driven Pooling. Computer Vision and Pattern Recognition. IEEE, pp. 7158-7167.He, Y., Chiu, W.C., Keuper, M., Fritz, M.: Std2p: Rgbd semantic segmentation using spatio-temporal data-driven pooling. In: CVPR. (2017)...
2020/December - update some recent papers (PAMI, PRL, arXiv, ACCV) of RGBD semantic segmentation. 2021/February - update some recent papers (TMM, NeurIPS, arXiv) of RGBD semantic segmentation. 2021/April - update some recent papers (CVPR2021, ICRA2021, IEEE SPL, arXiv) of RGBD semantic...
Barchid/RGBD-Seg master 1Branch 0Tags Code README License ESANet: Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis This repository contains the code to our paperEfficient RGB-D Semantic Segmentation for Indoor Scene Analysis.
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 3D spatial information separately. This solution greatly increases the inference ti...