# Revisiting Active Perception

arXiv: https://arxiv.org/abs/1603.02729 · HTML: https://mlsanity.com/paper/1603.02729/

## Key facts

- Cited by 94 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Mar 2016.

## Built on by (most cited first, 30 of 94)

- [Rapid Exploration for Open-World Navigation with Latent Goal Models](https://mlsanity.com/paper/2104.05859/) (2021)
- [Adaptive Rotated Convolution for Rotated Object Detection](https://mlsanity.com/paper/2303.07820/) (2023)
- [Eye, Robot: Learning to Look to Act with a BC-RL Perception-Action Loop](https://mlsanity.com/paper/2506.10968/) (2025)
- [A Survey on Human-aware Robot Navigation](https://mlsanity.com/paper/2106.11650/) (2021)
- [Safe Occlusion-aware Autonomous Driving via Game-Theoretic Active Perception](https://mlsanity.com/paper/2105.08169/) (2021)
- [Learning Active Camera for Multi-Object Navigation](https://mlsanity.com/paper/2210.07505/) (2022)
- [How to select and use tools? : Active Perception of Target Objects Using Multimodal Deep Learning](https://mlsanity.com/paper/2106.02445/) (2021)
- [Evidential Active Recognition: Intelligent and Prudent Open-World Embodied Perception](https://mlsanity.com/paper/2311.13793/) (2023)
- [Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task](https://mlsanity.com/paper/2211.05039/) (2022)
- [On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation](https://mlsanity.com/paper/2112.07173/) (2021)
- [Active Visuo-Haptic Object Shape Completion](https://mlsanity.com/paper/2203.09149/) (2022)
- [ActiView: Evaluating Active Perception Ability for Multimodal Large Language Models](https://mlsanity.com/paper/2410.04659/) (2024)
- [VISO-Grasp: Vision-Language Informed Spatial Object-centric 6-DoF Active View Planning and Grasping in Clutter and Invisibility](https://mlsanity.com/paper/2503.12609/) (2025)
- [Active-Perceptive Motion Generation for Mobile Manipulation](https://mlsanity.com/paper/2310.00433/) (2023)
- [The Artificial Intelligence behind the winning entry to the 2019 AI Robotic Racing Competition](https://mlsanity.com/paper/2109.14985/) (2021)
- [Visual-Tactile Cross-Modal Data Generation using Residue-Fusion GAN with Feature-Matching and Perceptual Losses](https://mlsanity.com/paper/2107.05468/) (2021)
- [Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse](https://mlsanity.com/paper/2109.00810/) (2021)
- [VLA-Thinker: Boosting Vision-Language-Action Models through Thinking-with-Image Reasoning](https://mlsanity.com/paper/2603.14523/) (2026)
- [ActiveMimic: Egocentric Video Pretraining with Active Perception](https://mlsanity.com/paper/2606.06194/) (2026)
- [NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction](https://mlsanity.com/paper/2109.13859/) (2021)
- [OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics](https://mlsanity.com/paper/2203.00403/) (2022)
- [SGTM 2.0: Autonomously Untangling Long Cables using Interactive Perception](https://mlsanity.com/paper/2209.13706/) (2022)
- [Interactive Benchmarks](https://mlsanity.com/paper/2603.04737/) (2026)
- [Next-Best-View Prediction for Active Stereo Cameras and Highly Reflective Objects](https://mlsanity.com/paper/2202.13263/) (2022)
- [Active inference and deep generative modeling for cognitive ultrasound](https://mlsanity.com/paper/2410.13310/) (2024)
- [Thousand-Brains Systems: Sensorimotor Intelligence for Rapid, Robust Learning and Inference](https://mlsanity.com/paper/2507.04494/) (2025)
- [Reinforcement Learning for Active Perception in Autonomous Navigation](https://mlsanity.com/paper/2602.01266/) (2026)
- [SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models](https://mlsanity.com/paper/2602.04208/) (2026)
- [Active Perception Applied To Unmanned Aerial Vehicles Through Deep Reinforcement Learning](https://mlsanity.com/paper/2209.06336/) (2022)
- [Learning to Look: Seeking Information for Decision Making via Policy Factorization](https://mlsanity.com/paper/2410.18964/) (2024)

## Abstract (arXiv)

Despite the recent successes in robotics, artificial intelligence and computer vision, a complete artificial agent necessarily must include active perception. A multitude of ideas and methods for how to accomplish this have already appeared in the past, their broader utility perhaps impeded by insufficient computational power or costly hardware. The history of these ideas, perhaps selective due to our perspectives, is presented with the goal of organizing the past literature and highlighting the seminal contributions. We argue that those contributions are as relevant today as they were decades ago and, with the state of modern computational tools, are poised to find new life in the robotic perception systems of the next decade.