mlsanityData to 14 Oct 2026

Binocular Gaze Estimation with Single Camera and Single Light Source

arXiv 2607.05473 ↗First posted 6 Jul 2026cs.CV cs.AIcited by 0

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Abstract (arXiv)

According to commonly consented theories, the minimum hardware requirement for gaze tracker is one camera and two light sources to realize gaze estimation with free head movements. However, in some scenarios such as eye tracking on mobile devices, it is preferable to use less components, especially light sources. We propose a gaze estimation method with one camera and one light source. A "virtual light source" is introduced, which is geometrically placed symmetrically to the real light source with respect to the camera, and generates a "virtual glint" in the acquired image. We estimate the "virtual glint" by exploiting the relationship between the distance between two pupils and two glints in the captured image, and estimate the gaze with polynomial regression assuming two light sources are available. A new normalization factor for regression method is verified, which turns out to be practical for one-glint system. The performance is proved to be acceptable, while degradation is noticed compared to system with two actual light sources.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 22 references that are in the map. First posted on arXiv 6 Jul 2026.

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References · 21

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
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  4. 2022Editing Models with Task Arithmeticcited by 1,120
  5. 2023On-Policy Distillation of Language Models: Learning from Self-Generated Mistakescited by 939
  6. 2025Group-in-Group Policy Optimization for LLM Agent Trainingcited by 497
  7. 2025SWE-smith: Scaling Data for Software Engineering Agentscited by 285
  8. 2025SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?cited by 279
  9. 2017Asymmetric Actor Critic for Image-Based Robot Learningcited by 238
  10. 2026OpenClaw-RL: Train Any Agent Simply by Talkingcited by 90
  11. 2026Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agentscited by 64
  12. 2026Large-Scale Terminal Agentic Trajectory Generation from Dockerized Environmentscited by 33
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  3. 2026ClawGym: A Scalable Framework for Building Effective Claw Agentscited by 15
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  5. 2026KAT-Coder-V2 Technical Reportcited by 8
  6. 2026ClawEnvKit: Automatic Environment Generation for Claw-Like Agentscited by 8
  7. 2025KAT-Coder Technical Reportcited by 7
  8. 2026Skill-as-Pseudocode: Refactoring Skill Libraries to Pseudocode for LLM Agentscited by 4
  9. 2026DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agentscited by 3

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