Haoyang Li

Papers

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About

Haoyang Li is a rising researcher in computer vision and robotics, with a primary focus on Visual Place Recognition (VPR)—a critical capability for autonomous navigation and mapping. His most cited work, "Unified Depth-Guided Feature Fusion and Reranking for Hierarchical Place Recognition" (2025), addresses a fundamental limitation in existing VPR methods: their reliance on RGB-based features, which are vulnerable to appearance changes caused by lighting, weather, or seasonal variation. Li proposes a novel framework that integrates depth information with visual features, enabling more robust retrieval and correspondence matching. By fusing multimodal data and introducing a reranking mechanism, his approach significantly improves place recognition accuracy in challenging real-world environments. Though early in his career, his work has already garnered attention (3 citations), signaling its potential impact on the field. Li’s contributions are particularly relevant for autonomous vehicles, drones, and mobile robots that must operate reliably across diverse conditions. His research exemplifies a growing trend toward leveraging complementary sensor modalities to overcome the limitations of purely visual systems, marking him as a promising innovator in spatial AI and robotic perception.