Search Results for "images"

...The dense modeling of the scene is the result yielded by chaining two computer vision-based pipelines, “Structure-from-Motion” (SfM) and “Multi View Stereo” (MVS). Fusion of Multi-bracketing LDR images into HDR. Alignment of panorama images. Support for fisheye optics. Automatically estimate fisheye circle or manually edit it. Take advantage of motorized-head file. Easy to integrate in your Renderfarm System. Add specific rules to select the most suitable machines regarding CPU, RAM, GPU requirements of each Node.

Gaussian Splatting is the official implementation of “3D Gaussian Splatting for Real-Time Radiance Field Rendering,” a research project for reconstructing and rendering 3D scenes from collections of images. The system represents scenes as millions of optimized 3D Gaussians rather than traditional meshes or neural fields, allowing high-quality novel view synthesis with real-time rendering performance. It includes training scripts, rendering tools, scene conversion utilities, and viewers for inspecting generated results. The project is widely used in computer graphics, spatial capture, virtual production, research, and experimental 3D reconstruction workflows. ...

The Python Computer Graphics Kit is a collection of Python modules that contain the basic types and functions to be able to create 3D computer graphics images (focusing on Pixar's RenderMan interface).

...The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists of 15K annotated video clips supplemented with over 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes. In addition, to ensure geo-diversity, our dataset is collected from 10 countries across five continents. Along with the dataset, we are also sharing a 3D object detection solution for four categories of objects — shoes, chairs, mugs, and cameras.

...Each environment includes fully labeled 3D objects, allowing agents to perceive and interact with their surroundings through multiple sensory modalities including RGB images, depth maps, semantic segmentation masks, and top-down maps. The simulator is optimized for high-performance rendering, achieving thousands of frames per second to enable efficient large-scale training of RL agents. House3D has served as the foundation for several influential research projects such as RoomNav (for concept-based navigation) and Embodied Question Answering (EQA).

Python based application to render in background Blender projects (still images or animation). It provides also a server for remote control such as checking the render status or cancel/submit new jobs. Msi available for windows.

The Anvil is setting out to produce one strong platform for all media. Fluid work with major audio, video, raster/vector images, 3D formats and scripting languages will allow us to start from anywhere and temper out the masterpeice we needed.