ROS 2 Human detector
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Updated
Sep 13, 2024 - Python
ROS 2 Human detector
Novel framework for Zero-Shot Style Alignment in Text-to-Image generation, incorporating Multi-Modal Context-Awareness and Multi-Reference Style Alignment, using minimal attention sharing, ensuring consistent style transfer without fine-tuning.
This code converts a point cloud obtained by a Velodyne VLP16 3D-Lidar sensor into a depth image mono16.
LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".
depth image generation from image of monocular camera
TensorRT implementation of Depth-Anything V1, V2
PlaneFill: Fast Normal Map Generation and Plane Detection from Depth Images
Generate blur image with 3 types of blur `motion`, `lens`, and `gaussian` by using OpenCV.
Python scripts that demonstrate advanced techniques for processing and visualizing depth images.
vid23d Scallop transforms 2D video into 3D stereo SBS video using depth estimation and stereo pair generation. Utilizing deep learning and computer vision, it supports frame processing, audio merging, and enhanced visualization.
Optimized depth to pointcloud conversion in Python for ROS1
Real-Time 3D Semantic Reconstruction from 2D data
Code for generating the SLED dataset, as described in the "Learning to Estimate Two Dense Depths from LiDAR and Event Data" article
Contains the code and weights to our paper "Multi-Task Deep Learning for Depth-based Person Perception in Mobile Robotics" that was published on IROS 2020.
python RGB-D processing tool
Convert a single-file RecFusion sequence (*.rfs) to a collection of depth and colour PNG images.
Add a description, image, and links to the depth-image topic page so that developers can more easily learn about it.
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