Beast code in Giters

Code release for "Spatiotemporal Residual Networks for Video Action Recognition", NIPS16 & "Spatiotemporal Multiplier Networks for Video Action Recognition", CVPR17.

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video-nonlocal-net

Non-local Neural Networks for Video Classification

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pytorch-cifar

95.47% on CIFAR10 with PyTorch

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resnet-1k-layers

Deep Residual Networks with 1K Layers

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simclr

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

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tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

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big_transfer

Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.

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VideoMAEv2

[CVPR 2023] VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking

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VideoMAE

[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

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TimeSformer

The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"

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Test your prompts, agents, and RAGs. Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

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InternVideo

[ECCV2024] Video Foundation Models & Data for Multimodal Understanding

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mvit

Code Release for MViTv2 on Image Recognition.

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models

Models and examples built with TensorFlow

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ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

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ActionDetection-DBG

Code for AAAI2020 paper "Fast Learning of Temporal Action Proposal via Dense Boundary Generator"

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FunASR

A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.

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kornia

Geometric Computer Vision Library for Spatial AI

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mmaction2

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

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fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

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