--- language: - en license: mit metrics: - mean_iou tags: - Semantic_Future_Prediction - Video_Generation pipeline_tag: video-to-video --- # Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers (CVPR 2025) This model is described in the paper [Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers](https://huggingface.co/papers/2501.08303). Project Page: [https://futurist-cvpr2025.github.io](https://futurist-cvpr2025.github.io) ![teaser.png](https://cdn-uploads.huggingface.co/production/uploads/677272184d148b904333e874/nm6D0QZpagySIkWDg7Y4h.png) FUTURIST employs a multimodal visual sequence transformer to directly predict multiple future semantic modalities. We focus on two key modalities: semantic segmentation and depth estimation. - Key innovation 1: We introduce a VAE-free hierarchical tokenization process integrated directly into our transformer. This simplifies training, reduces computational overhead, and enables true end-to-end optimization - Key innovation 2: Our model features an efficient cross-modality fusion mechanism that improves predictions by learning synergies between different modalities (segmentation + depth) - Key innovation 3: We developed a novel multimodal masked visual modeling objective specifically designed for future prediction tasks We achieve state-of-the-art performance in future semantic segmentation on Cityscapes, with strong improvements in both short-term (0.18s) and mid-term (0.54s) predictions # Code https://github.com/Sta8is/FUTURIST # Demo: We provide 2 quick demos. - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1fS51KGb1nwDiLplVcM4stypQe3Qtb5iW?usp=sharing) - [Demo](https://github.com/Sta8is/FUTURIST/blob/main/demo.ipynb). # Citation: If you found Futurist useful in your research, please consider starring ⭐ us on GitHub and citing 📚 us in your research! ``` @InProceedings{Karypidis_2025_CVPR, author = {Karypidis, Efstathios and Kakogeorgiou, Ioannis and Gidaris, Spyros and Komodakis, Nikos}, title = {Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers}, booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)}, month = {June}, year = {2025}, pages = {3793-3803} @article{karypidis2025advancingsemanticfutureprediction, title={Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers}, author={Efstathios Karypidis and Ioannis Kakogeorgiou and Spyros Gidaris and Nikos Komodakis}, year={2025}, journal={arXiv:2501.08303} url={https://arxiv.org/abs/2501.08303}, } ```