Tias Guns of KU Leuven presents "Prediction + Optimisation: without and with decision-focused learning" at IPAM's Artificial Intelligence and Discrete Optimization Workshop.

Delve into three key approaches for augmenting optimization modeling with AI: preference learning in Vehicle Routing Problems, end-to-end decision-focused learning, and explanation …

Tias Guns of KU Leuven presents "Prediction + Optimisation: without and with decision-focused learning" at IPAM's Artificial Intelligence and Discrete Optimization Workshop.

To address this limitation, this paper proposes the first AutoRegression-Free (AR- Free) video prediction framework using diffusion models. Different from an autoregressive video prediction …

🎯 Production-ready implementation of video prediction models using PyTorch. Features Enhanced ConvLSTM with temporal attention, PredRNN with spatiotemporal memory, and Transformer …

Our method can produce plausible video prediction results in diverse scenarios without external training, such as driving scenes, human motion, animation, and natural scenes. We use red …

We show qualitative results of the video predictions achieved by our SAVP method, our GAN and VAE variants, and other approaches. SV2P is prior work from Babaeizadeh et al. 2017, while …

In this paper, we constructed a deep neural network Frame Prediction Network (FPNet-OF) with multiple-branch inputs (optical flow and original frame) to predict the future video frame by …

Jun 27, 2022 · Inspired by the photo-realistic results of video frame interpolation, we present a new optimization framework for video prediction via video frame interpolation, in which we …

Dec 16, 2024 · Free video prediction AI tools for forecasting future frames in video sequences, optimizing content creation for film, games, and analysis. FCVG can create smooth video …