Search Results for "spatial temporal database"
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Showing 23 open source projects for "spatial temporal database"
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SlowFast
Video understanding codebase from FAIR for reproducing video models
SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without excessive computational cost. ... -
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Step-Video-T2V
State-of-the-art (SoTA) text-to-video pre-trained model
Step-Video-T2V is a state-of-the-art text-to-video foundation model developed to generate videos from natural-language prompts; its 30B-parameter architecture is designed to produce coherent, temporally extended video sequences — up to around 204 frames — based on input text. Under the hood it uses a compressed latent representation (a Video-VAE) to reduce spatial and temporal redundancy, and a denoising diffusion (or similar) process over that latent space to generate smooth, plausible motion and visuals. The model handles bilingual input (e.g. English and Chinese) thanks to dual encoders, and supports end-to-end text-to-video generation without requiring external assets. Its training and generation pipeline includes techniques like flow-matching, full 3D attention for temporal consistency, and fine-tuning approaches (e.g. video-based DPO) to improve fidelity and reduce artifacts. ... -
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SeedVR2 Upscaler ComfyUI
Official SeedVR2 Video Upscaler for ComfyUI
ComfyUI-SeedVR2 Video Upscaler is an open-source integration node for the ComfyUI workflow environment that brings the advanced SeedVR2 video upscaling and restoration model directly into visual AI pipelines. This project packages the SeedVR2 architecture as a custom node for ComfyUI, letting users upscale low-resolution video or imagery inside a node-based interface without needing to write code manually. The underlying SeedVR2 model is known for delivering high-quality video enhancement... -
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HY-World 1.5
A Systematic Framework for Interactive World Modeling
...It blends advanced reasoning with multimodal synthesis, enabling agents to describe scenes, generate context-appropriate responses, and contribute to narrative or gameplay flows. The underlying framework typically supports large-context state tracking across extended interactions, blending temporal and spatial multimodal signals. -
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Qwen-2.5-VL
Qwen2.5-VL is the multimodal large language model series
Qwen2.5 is a series of large language models developed by the Qwen team at Alibaba Cloud, designed to enhance natural language understanding and generation across multiple languages. The models are available in various sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B parameters, catering to diverse computational requirements. Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation... -
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Pelican
Static site generator that supports Markdown and reST syntax
...Pelican considers “articles” to be chronological content, such as posts on a blog, and thus associated with a date. The idea behind “pages” is that they are usually not temporal in nature and are used for content that does not change very often (e.g., “About” or “Contact” pages). Pelican tries to be smart enough to get the information it needs from the file system. -
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QUADE Protocol Suite
A new protocol and browser for it.
Welcome to a new standard for secure communications. Deploy a brand new protocol based on central ddns and peer 2 peer content sharing with central site database for backup. This suite allows the customization of the entire process: so what this is, is a new standard of encryption upon the known and standard RSA and AES with Quadrant Wave Transport Protocol a new standard of polymorphic encryption with temporal keys and mutating ciphertext. HOW TO USE: Extract to a folder on desktop Place the files in switch and website template into the main folder for your central website. ... -
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pyDaSSQLiteMan
An easy way to manage SQLite databases and query CSV files
Welcome to the project page for pyDaSSQLiteMan (Python Data and SQLite Manager). This application is a Python Tkinter application designed to enable easy SQLite database file manipulation, and an easy method to run SQL styled queries on CSV files. If you're not downloading the pre-compiled executable you will need Python to run this app. You can download it from http://www.python.org/ . I'd recommend something after version 3. Testing has been Windows based. SQLite is a free database... -
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NuPIC
Numenta platform for intelligent computing
The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources. For more information, see numenta.org or the NuPIC Forum. If you want to build the dependent nupic.bindings from source, you should build and install from nupic.core prior to installing nupic (since a PyPI release will be installed if nupic.bindings isn't yet installed). ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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BEVFormer
Implementation of BEVFormer, a camera-only framework
...In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. To aggregate spatial information, we design spatial cross-attention that each BEV query extracts the spatial features from the regions of interest across camera views. For temporal information, we propose temporal self-attention to recurrently fuse the history BEV information. ... -
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ECOLOG
A database management system for ecological field surveys
ECOLOG is a specimen-based, cross-platform relational database management system, aimed at the storage, retrieval and preliminary analysis of data on sites, species, and specimens gathered in ecological field surveys and biodiversity inventories. The main goal of ECOLOG is to make the data gathered in ecological field surveys readily accessible, providing lists of species collected in the study area and informations on habitat preferences, abundance or rarity of a given species, biometrics, morphology, dominance, and spatial location of each specimen collected in the field. -
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TimeSformer
The official pytorch implementation of our paper
...TimeSformer was influential in showing that pure transformer architectures—without convolutional backbones—can perform strongly on video classification tasks. Its flexible attention design allows experimenting with different factoring (spatial-then-temporal, joint, etc.) to trade off compute, memory, and accuracy. -
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BasicSR
Winning Solution in NTIRE19 Challenges on Video Restoration
...By fusing spatial and temporal context, EDVR produces significantly improved visual quality in restored videos compared with approaches that treat each frame independently. -
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Optimized Storage for temporal Data
open Optimized Storage of time series data
Beta version. Base class for optimized storage of time series data. Uses any kind of relational database. Cross plateform with multiple languages (C++, C#, Java). Conditional storage based on value variation : DeltaValue and DeltaTime params. Get back data without losts. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. ... -
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Five video classification methods
Code that accompanies my blog post outlining five video classification
Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and a whole whack load of hyperparameters we don’t have to worry about. ... -
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EDCC-CNG
Exploration and categorization of CREs and CRMs
Cis-regulatory elements (CREs) and cis-regulatory modules (CRMs) play an important role in temporal and spatial regulation of gene expression, which is a common process in eukaryotic organisms. We developed two programs that serve as exploratory tools in the analysis of CRM-mediated control of gene expression: “Exploration of Distinctive CREs and CRMs” (EDCC) and “CRM Network Generator” (CNG). EDCC correlates the presence and positions of CREs/CRMs with gene expression data and identifies candidate regulatory elements for further functional analysis. ... -
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Lip Reading
Cross Audio-Visual Recognition using 3D Architectures
The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the... -
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PAGC is a command line and web service C library for performing postal address geocoding. A postal address geocoder takes a sufficiently detailed postal addresses and produces a digital map that displays the spatial location of those addresses.
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This project provides a Fortran90 library and a python module for singular spectrum analyses such as PCA/EOF or MSSA. It is intended for people interested, for example, in analysing climate or financial variability.
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The Virtual Commons (http://commons.asu.edu) is an open software initiative devoted to computational experiments on collective action and resource governance and funded by Arizona State University's Center for Behavior, Institutions, and the Environment (http://cbie.asu.edu). NOTE: we've moved our development to GitHub at https://github.com/virtualcommons - please look for the latest versions there.
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Space Time Analysis of Regional Systems: Combines a suite of geocomputational and dynamic visualization modules for the exploratory analysis of data measured for spatial and temporal units.
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Gigabyte-scale persistent object Store in C++. Able to intern and persist arbitrary ELF loadble objects. Convenient class library (Lists, Strings, Dicts, Namespaces, etc.) optimised for spatial locality of reference. Virtual machine toolkit.
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