Mastering Atari with Discrete World Models
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Updated
Jan 21, 2023 - Python
Mastering Atari with Discrete World Models
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
The pytorch implementation of our CVPR 2023 paper "Conditional Image-to-Video Generation with Latent Flow Diffusion Models"
Stochastic Adversarial Video Prediction
You can easily calculate FVD, PSNR, SSIM, LPIPS for evaluating the quality of generated or predicted videos.
Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)
[ICLR 2024] MogaNet: Efficient Multi-order Gated Aggregation Network
e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond
Code release for "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics" (CVPR 2019)
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
Video Predicting using ConvLSTM and pytorch
Code release for ICLR 2023 paper: SlotFormer on object-centric dynamics models
Official repository for "iVideoGPT: Interactive VideoGPTs are Scalable World Models" (NeurIPS 2024), https://arxiv.org/abs/2405.15223
Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all cropped spatio-temporally and filmed from a surveillance-camera like position.
Official PyTorch implementation of "Video Prediction Recalling Long-term Motion Context via Memory Alignment Learning" (CVPR 2021 Oral)
Official implementation of the paper Stochastic Latent Residual Video Prediction
Pytorch implementations of ConvLSTM and ConvGRU modules with examples
About Code release for "MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions" (CVPR 2021) https://arxiv.org/abs/2103.02243
A comprehensive list of papers for the definition of World Models and using World Models for General Video Generation, Embodied AI, and Autonomous Driving, including papers, codes, and related websites.
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