Xin’s picks of the day (Tuesday): Xin Qiao is an assistant professor at Xi’an Jiaotong University, China. His research focuses on 3D imaging, computational imaging, and deep learning, with particular interest in making depth sensing more accurate and interpretable for real-world applications such as under-display cameras and multimodal perception in complex environments. 2B-3 Knowledge Distillation for Learned Image Compression 2- 53 PHATNet: A Physics-guided Haze Transfer Network for Domain-adaptive … 2- 94 FiffDepth: Feed-forward Transformation of Diffusion-Based Generators … 2-101 DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor … 2-112 CO2-Net: A Physics-Informed Spatio-Temporal Model for Global Surface … For today, Tuesday 21 2 Xin’s Picks DAILY ICCV Tuesday “Hi! My work at ICCV 2025, “Learnable Fractional Reaction-Diffusion Dynamics for Under-Display ToF Imaging and Beyond,” presents a hybrid framework that integrates physical modeling with deep learning. We encode a time-fractional reaction-diffusion equation into the network to capture long-term dynamics and introduce an efficient continuous convolution operator for interpretable depth restoration. The framework achieves state-of-the-art performance on multiple ToF and RGB-D benchmarks. Unfortunately, I’m unable to attend ICCV 2025 due to visa issues, but I’m thrilled that our work will still be presented today [Poster 2-99]. Please stop by to learn more about fractional dynamics and physicsguided depth restoration, and feel free to drop me an email if you’d like to discuss. I wish everyone an inspiring and sunny week in Hawaii!” Oral: Posters:
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