# Deep Learning Perspective of Scene Understanding in Autonomous Robots

arXiv: https://arxiv.org/abs/2512.14020 · HTML: https://mlsanity.com/paper/2512.14020/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 56 of its 95 references that are in the map.
- First posted on arXiv 16 Dec 2025.

## Builds on (most cited first, 30 of 56)

- [NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)](https://mlsanity.com/paper/2210.00379/) (2022)
- [Convergence of Edge Computing and Deep Learning: A Comprehensive Survey](https://mlsanity.com/paper/1907.08349/) (2019)
- [Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things](https://mlsanity.com/paper/2011.08612/) (2020)
- [Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review](https://mlsanity.com/paper/2004.05224/) (2020)
- [An Outlook into the Future of Egocentric Vision](https://mlsanity.com/paper/2308.07123/) (2023)
- [How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Survey](https://mlsanity.com/paper/2402.13255/) (2024)
- [A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks](https://mlsanity.com/paper/2306.07303/) (2023)
- [Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving](https://mlsanity.com/paper/2405.17426/) (2024)
- [Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform](https://mlsanity.com/paper/2008.09162/) (2020)
- [A Survey on Socially Aware Robot Navigation: Taxonomy and Future Challenges](https://mlsanity.com/paper/2311.06922/) (2023)
- [Explainable Deep Reinforcement Learning: State of the Art and Challenges](https://mlsanity.com/paper/2301.09937/) (2023)
- [Robotic Perception of Transparent Objects: A Review](https://mlsanity.com/paper/2304.00157/) (2023)
- [NavFormer: A Transformer Architecture for Robot Target-Driven Navigation in Unknown and Dynamic Environments](https://mlsanity.com/paper/2402.06838/) (2024)
- [Video Anomaly Detection in 10 Years: A Survey and Outlook](https://mlsanity.com/paper/2405.19387/) (2024)
- [On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation](https://mlsanity.com/paper/2010.06626/) (2020)
- [Advances in Inference and Representation for Simultaneous Localization and Mapping](https://mlsanity.com/paper/2103.05041/) (2021)
- [Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments](https://mlsanity.com/paper/2312.07935/) (2023)
- [Transformer-Based Sensor Fusion for Autonomous Driving: A Survey](https://mlsanity.com/paper/2302.11481/) (2023)
- [Semantic Mapping in Indoor Embodied AI -- A Survey on Advances, Challenges, and Future Directions](https://mlsanity.com/paper/2501.05750/) (2025)
- [A Review of Transformer-Based Models for Computer Vision Tasks: Capturing Global Context and Spatial Relationships](https://mlsanity.com/paper/2408.15178/) (2024)
- [Visual SLAM: What are the Current Trends and What to Expect?](https://mlsanity.com/paper/2210.10491/) (2022)
- [ClearDepth: Enhanced Stereo Perception of Transparent Objects for Robotic Manipulation](https://mlsanity.com/paper/2409.08926/) (2024)
- [A Survey of FPGA-Based Robotic Computing](https://mlsanity.com/paper/2009.06034/) (2020)
- [A Review on Visual-SLAM: Advancements from Geometric Modelling to Learning-based Semantic Scene Understanding](https://mlsanity.com/paper/2209.05222/) (2022)
- [World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving](https://mlsanity.com/paper/2507.12762/) (2025)
- [Joint Perception and Prediction for Autonomous Driving: A Survey](https://mlsanity.com/paper/2412.14088/) (2024)
- [Uncertainty-guided Optimal Transport in Depth Supervised Sparse-View 3D Gaussian](https://mlsanity.com/paper/2405.19657/) (2024)
- [Query-based Semantic Gaussian Field for Scene Representation in Reinforcement Learning](https://mlsanity.com/paper/2406.02370/) (2024)
- [Probabilistic Robustness in Deep Learning: A Concise yet Comprehensive Guide](https://mlsanity.com/paper/2502.14833/) (2025)
- [Towards Robust Part-aware Instance Segmentation for Industrial Bin Picking](https://mlsanity.com/paper/2203.02767/) (2022)

## Abstract (arXiv)

This paper provides a review of deep learning applications in scene understanding in autonomous robots, including innovations in object detection, semantic and instance segmentation, depth estimation, 3D reconstruction, and visual SLAM. It emphasizes how these techniques address limitations of traditional geometric models, improve depth perception in real time despite occlusions and textureless surfaces, and enhance semantic reasoning to understand the environment better. When these perception modules are integrated into dynamic and unstructured environments, they become more effective in decisionmaking, navigation and interaction. Lastly, the review outlines the existing problems and research directions to advance learning-based scene understanding of autonomous robots.