Search Results for "2d"
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Showing 59 open source projects for "2d"
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InsightFace
State-of-the-art 2D and 3D Face Analysis Project
State-of-the-art deep face analysis library. InsightFace is an open-source 2D&3D deep face analysis library. InsightFace is an integrated Python library for 2D&3D face analysis. InsightFace efficiently implements a wide variety of state-of-the-art algorithms for face recognition, face detection, and face alignment, which are optimized for both training and deployment. Research institutes and industrial organizations can get benefits from InsightFace library. -
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Agent Sprite Forge
Agent Skill for generating 2D sprite sheets and map, transparent PNG
...Its architecture is designed around automation and repeatability, enabling developers to generate large batches of visual assets through structured prompt workflows. Overall, agent-sprite-forge acts as an AI-assisted creative tool for accelerating 2D game art production and experimentation. -
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Mesh R-CNN
code for Mesh R-CNN, ICCV 2019
...Built on top of Detectron2 and PyTorch3D, Mesh R-CNN enables end-to-end 3D mesh prediction directly from single RGB images. The model learns to detect, segment, and reconstruct detailed 3D mesh representations of objects in natural images, bridging the gap between 2D perception and 3D understanding. Unlike voxel-based or point-based approaches, Mesh R-CNN uses a differentiable mesh representation, allowing it to efficiently refine surface geometry while maintaining high spatial detail. The system combines 2D detection from Mask R-CNN with 3D reasoning modules that output full mesh reconstructions aligned with the input image. ... -
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Flow Matching
A PyTorch library for implementing flow matching algorithms
...The library supports both continuous-time flows (via differential equations) and discrete-time analogues, giving flexibility in design and tradeoffs. It provides examples across modalities (images, toy 2D distributions) to help users understand how to apply flow matching in practice. The codebase includes notebooks illustrating 2D flow matching, discrete flows, and Riemannian flow matching on curved manifolds (e.g. flat torus) for non-Euclidean support. -
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Depth Anything 3
Recovering the Visual Space from Any Views
Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography, AR/VR content creation, robotics perception, and 3D reconstruction workflows, making it versatile across industries and research domains. ... -
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OpenClaw Office
OpenClaw Office is the visual monitoring and management frontend
OpenClaw Office is a visual monitoring and management interface designed for the OpenClaw multi-agent system, providing an immersive and interactive way to observe and control autonomous AI agents. It presents agent activity through a virtual office environment, where each agent is represented as an animated entity within a 2D or 3D workspace. The platform enables real-time visualization of agent states, interactions, and workflows, making complex multi-agent coordination easier to understand and debug. Users can observe communication flows between agents through visual connections, track token usage and operational costs, and analyze performance through integrated dashboards and charts. ... -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. ... -
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Minigrid
Simple and easily configurable grid world environments
Minigrid is a lightweight, minimalistic grid-world environment library for reinforcement learning (RL) research. It provides a suite of simple 2D grid-based tasks (e.g., navigating mazes, unlocking doors, carrying keys) where an agent moves in discrete steps and interacts with objects. The design emphasizes speed (agents can run thousands of steps per second), low dependency overhead, and high customizability — making it easy to define new maps, new tasks, or wrappers. It supports the Gymnasium-style environment API so that RL researchers can plug it into their existing frameworks and algorithms with minimal adaptation. ... -
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Qwen3-VL
Qwen3-VL, the multimodal large language model series by Alibaba Cloud
Qwen3-VL is the latest multimodal large language model series from Alibaba Cloud’s Qwen team, designed to integrate advanced vision and language understanding. It represents a major upgrade in the Qwen lineup, with stronger text generation, deeper visual reasoning, and expanded multimodal comprehension. The model supports dense and Mixture-of-Experts (MoE) architectures, making it scalable from edge devices to cloud deployments, and is available in both instruction-tuned and... -
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1D Visual Tokenization and Generation
This repo contains the code for 1D tokenizer and generator
The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact representation makes sampling and generation many times faster compared to previous tokenization methods (claims of ~410× speedups relative to heavyweight models) while still producing competitive image quality. ... -
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SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image... -
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AliceVision
3D Computer Vision Framework
AliceVision is an open-source photogrammetric computer vision framework designed to reconstruct detailed 3D scenes and camera motion from collections of images or videos. It provides a complete pipeline for structure-from-motion (SfM), multi-view stereo (MVS), and mesh generation, allowing users to convert 2D imagery into accurate 3D models. The framework is built with a strong emphasis on research-grade algorithms while maintaining the robustness required for production environments, making it suitable for industries such as visual effects, cultural heritage preservation, and robotics. AliceVision is modular, enabling developers to use individual components or customize the pipeline for specific workflows, including panorama stitching and camera tracking. ... -
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Sprite Fusion Pixel Snapper
A tool to snap pixels to a perfect grid
Sprite Fusion Pixel Snapper is a utility designed to eliminate sub-pixel rendering issues that often arise in pixel art, UI icons, and 2D sprite graphics when displayed on screens with high DPI or during motion animations. The tool works by adjusting sprite rendering coordinates and texture sampling so that every pixel aligns cleanly to the screen’s pixel grid, avoiding blurring, distortion, or unintended smoothing artifacts. This is especially important in pixel art games, retro-styled interactive media, or precise UI designs where crisp edges and predictable alignment are essential. ... -
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DeepLabCut
Implementation of DeepLabCut
DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. -
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Godot RL Agents
An Open Source package that allows video game creators
godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot. -
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Animated Drawings
Code to accompany "A Method for Animating Children's Drawings"
AnimatedDrawings is a framework that converts user sketches or line drawings into fully animated 2D motion sequences using learned motion priors. The idea is that you draw a simple static figure (stick figure, silhouette, or contour lines), and the system produces plausible skeletal motion (walking, jumping, dancing) that adheres to the drawn shape constraints. The architecture separates shape embedding (to understand user-drawn geometry) from motion embedding / generation (to produce temporally coherent movement). ... -
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PyTorch3D
PyTorch3D is FAIR's library of reusable components for deep learning
...Researchers use it for tasks like shape generation, reconstruction, view synthesis, and visual reasoning. PyTorch3D also includes utilities for loading, transforming, and sampling 3D assets, so models can be trained end-to-end from 2D supervision or partial data. Its modular design allows easy extension—components like differentiable rasterizers, mesh blending, or signed distance field (SDF) modules can be swapped or combined to test new architectures quickly. -
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Image Extender
Seamlessly extend any image in any direction with AI
Image Extender is an open-source web app for AI outpainting and 2D game-art generation. It lets users extend an image in any direction while using Poisson blending to reduce visible seams between the original and generated areas. The app uses Gemini image models through OpenRouter and keeps the user’s OpenRouter key in the browser. It includes a best-of-three variant picker so users can choose the cleanest extension result. -
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49 Agents IDE
Open-source 2D IDE for managing AI agents in native CLIs
49Agents is an open-source “agentic IDE” that reimagines how developers interact with multiple AI agents, terminals, and development environments by placing everything onto a single infinite, zoomable canvas. Instead of relying on traditional tab-based workflows, it provides a spatial interface where terminals, editors, Git views, and monitoring tools coexist as movable panes, enabling users to manage complex multi-agent systems visually and intuitively. The platform is designed to work... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared... -
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Video Diffusion - Pytorch
Implementation of Video Diffusion Models
...Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. It uses a special space-time factored U-net, extending generation from 2D images to 3D videos. 14k for difficult moving mnist (converging much faster and better than NUWA) - wip. Any new developments for text-to-video synthesis will be centralized at Imagen-pytorch. For conditioning on text, they derived text embeddings by first passing the tokenized text through BERT-large. You can also directly pass in the descriptions of the video as strings, if you plan on using BERT-base for text conditioning. ... -
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OpenKM Document Management - DMS
Document Management System and Content Management System
OpenKM Community Edition is a free Document Management System (DMS) that helps businesses control the production, storage, management and distribution of electronic documents, boosting effectiveness and productivity. It integrates document management, collaboration and advanced search into one easy-to-use solution, including administration tools for user roles, access control, security levels, activity logs and automation setup. With OpenKM Community Edition you can: Collect information... -
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Make-A-Video - Pytorch (wip)
Implementation of Make-A-Video, new SOTA text to video generator
...Passing in images (if one were to pretrain on images first), both temporal convolution and attention will be automatically skipped. In other words, you can use this straightforwardly in your 2d Unet and then port it over to a 3d Unet once that phase of the training is done. -
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Stable-Dreamfusion
Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion
A pytorch implementation of the text-to-3D model Dreamfusion, powered by the Stable Diffusion text-to-2D model. This project is a work-in-progress and contains lots of differences from the paper. The current generation quality cannot match the results from the original paper, and many prompts still fail badly! Since the Imagen model is not publicly available, we use Stable Diffusion to replace it (implementation from diffusers). Different from Imagen, Stable-Diffusion is a latent diffusion model, which diffuses in a latent space instead of the original image space. ... -
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PIFuHD
High-Resolution 3D Human Digitization from A Single Image
PIFuHD (Pixel-Aligned Implicit Function for 3D human reconstruction at high resolution) is a method and codebase to reconstruct high-fidelity 3D human meshes from a single image. It extends prior PIFu work by increasing resolution and detail, enabling fine geometry in cloth folds, hair, and subtle surface features. The method operates by learning an implicit occupancy / surface function conditioned on the image and camera projection; at inference time it queries dense points to reconstruct a...