Blender Add-on to edit RenderWare and GTA Formats

The source code of CVPR 2020 paper "Multi-Scale Boosted Dehazing Network with Dense Feature Fusion"

DFF (Digital Forensics Framework) is a Forensics Framework coming with command line and graphical interfaces. DFF can be used to investigate hard drives and volatile memory and create reports about user and system activities.

The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.

Code for Dynamic Feature Fusion for Semantic Edge Detection https://arxiv.org/abs/1902.09104

Official implementation for HybridDepth Model [WACV 2025, ISMAR 2024]

A micro library for diffing and patching JSON objects using a compact diff format

Standard Cell Library based Memory Compiler using FF/Latch cells

GTAV > GTASA resource converter. Converts YTD/YDR/YDD/YFT resources to DFF/TXD and generates COL files.

Conventional Depth from Focus(DfF) estimation with slight focus variations in image sequences

No description available

Official implementation of Sim-to-Real Transfer via 3D Feature Fields for Vision-and-Language Navigation (CoRL'24).

No description available

This Denoising Force Field (DFF) codebase provides a Pytorch framework for the method presented in Two for one: Diffusion models and force fields for coarse-grained molecular dynamics.

P3DFFT stands for Parallel Three-Dimensional Fast Fourier Transforms. It is a library for large-scale computer simulations on parallel platforms. It implements 3D FFT and related algorithms such as Chebyshev transform (an important class of algorithm for simulations in a wide range of fields). P3DFFT uses 2D, or pencil, decomposition. For more information:

Deep Feature Factorization

Depth and DOF Cues Make A Better Defocus Blur Detector

[ECCV2022] Official implementation of 'Learning Depth from Focus in the Wild'

No description available

[CVPR'22] DFVDFF: Deep Depth from Focus with Differential Focus Volume

No description available

WebGL2.0 2DFFT interactive live demo playground

A deep learning-based method for hyperspectral image classification, which published in IEEE Trans. Geosci. Remote Sens., 2018.

Towards Domain Free Transformer for Generalized EEG Pre-training

Curved Layer Fused Filament Fabrication (CLFFF) Algorithm that produces G-Code with normal vectors for 5 axis 3d printing. Uses variable layer height.

P3DFFT++ (a.k.a. P3DFFT v. 3) is a new generation of P3DFFT library that aims to provide a comprehensive framework for simulating multiscale phenomena. It takes the essence of P3DFFT further by creating an extensible, modular structure uniquely adaptable to a greater range of use cases. The users can specify in detail what kind of data layout they would like to use, both in terms of local memory ordering and the processor layout. Just like P3DFFT, P3DFFT++ is a distributed software package, using MPI as the primary method for interprocessor commubnication. It supports 1D, 2D and 3D (to come soon) domain decomposition schemes. As P3DFFT, P3DFFT++ also relies on lower-level libraries, for example FFTW to perform optimized 1D FFTs. Unlike P3DFFT, which was written in Fortran90, P3DFFT++ is written in C++. Interfaces are provided for C and Fortran. To learn about using the code the user is encouraged to study example programs in C++, C and FORTRAN subdirectories. Please e-mail Dmitry Pekurovsky (dmitry@sdsc.edu) for any questions or suggestions. Software contributions are welcome, assuming they follow the main ideas of the framework.

A complete hand-held Depth from Focus (DfF) pipeline

monitor changes as AI agents modify your codebase

Codes for C2DFF-Net for Object Detection in Multimodal Remote Sensing Images.

GC/Wii homebrew application used for playing back dff files recorded by Dolphin on real hardware.