# Pseudo Dataset Generation for Out-of-Domain Multi-Camera View Recommendation

arXiv: https://arxiv.org/abs/2410.13585 · HTML: https://mlsanity.com/paper/2410.13585/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 20 references that are in the map.
- First posted on arXiv 17 Oct 2024.

## Builds on (most cited first, 14 of 14)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Representation Learning with Contrastive Predictive Coding](https://mlsanity.com/paper/1807.03748/) (2018)
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://mlsanity.com/paper/1911.05722/) (2019)
- [Temporal Segment Networks: Towards Good Practices for Deep Action Recognition](https://mlsanity.com/paper/1608.00859/) (2016)
- [TransNet V2: An effective deep network architecture for fast shot transition detection](https://mlsanity.com/paper/2008.04838/) (2020)
- [Condensed Movies: Story Based Retrieval with Contextual Embeddings](https://mlsanity.com/paper/2005.04208/) (2020)
- [A Unified Framework for Shot Type Classification Based on Subject Centric Lens](https://mlsanity.com/paper/2008.03548/) (2020)
- [Fast Video Shot Transition Localization with Deep Structured Models](https://mlsanity.com/paper/1808.04234/) (2018)
- [Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows](https://mlsanity.com/paper/2210.08737/) (2022)
- [Smart Director: An Event-Driven Directing System for Live Broadcasting](https://mlsanity.com/paper/2201.04024/) (2022)
- [Learning Sports Camera Selection from Internet Videos](https://mlsanity.com/paper/1809.02854/) (2018)

## Built on by (most cited first, 2 of 2)

- [When and How to Cut Classical Concerts? A Multimodal Automated Video Editing Approach](https://mlsanity.com/paper/2510.05661/) (2025)
- [A Dual-Transformer for Multi-Camera View Recommendation](https://mlsanity.com/paper/2608.25601/) (2026)

## Abstract (arXiv)

Multi-camera systems are indispensable in movies, TV shows, and other media. Selecting the appropriate camera at every timestamp has a decisive impact on production quality and audience preferences. Learning-based view recommendation frameworks can assist professionals in decision-making. However, they often struggle outside of their training domains. The scarcity of labeled multi-camera view recommendation datasets exacerbates the issue. Based on the insight that many videos are edited from the original multi-camera videos, we propose transforming regular videos into pseudo-labeled multi-camera view recommendation datasets. Promisingly, by training the model on pseudo-labeled datasets stemming from videos in the target domain, we achieve a 68% relative improvement in the model's accuracy in the target domain and bridge the accuracy gap between in-domain and never-before-seen domains.