Search Results for author: Shilin Zhu

Found 8 papers, 4 papers with code

Robust Multimodal Vehicle Detection in Foggy Weather Using Complementary Lidar and Radar Signals

1 code implementation CVPR 2021 Kun Qian, Shilin Zhu, Xinyu Zhang, Li Erran Li

Vehicle detection with visual sensors like lidar and camera is one of the critical functions enabling autonomous driving.

Autonomous Driving

Photon-Driven Neural Path Guiding

no code implementations5 Oct 2020 Shilin Zhu, Zexiang Xu, Tiancheng Sun, Alexandr Kuznetsov, Mark Meyer, Henrik Wann Jensen, Hao Su, Ravi Ramamoorthi

To fully make use of our deep neural network, we partition the scene space into an adaptive hierarchical grid, in which we apply our network to reconstruct high-quality sampling distributions for any local region in the scene.

Survey: Machine Learning in Production Rendering

no code implementations26 May 2020 Shilin Zhu

In the past few years, machine learning-based approaches have had some great success for rendering animated feature films.

BIG-bench Machine Learning Denoising

Deep Photon Mapping

no code implementations25 Apr 2020 Shilin Zhu, Zexiang Xu, Henrik Wann Jensen, Hao Su, Ravi Ramamoorthi

This network is easy to incorporate in many previous photon mapping methods (by simply swapping the kernel density estimator) and can produce high-quality reconstructions of complex global illumination effects like caustics with an order of magnitude fewer photons compared to previous photon mapping methods.

Denoising Density Estimation

Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness

1 code implementation CVPR 2020 Shuo Cheng, Zexiang Xu, Shilin Zhu, Zhuwen Li, Li Erran Li, Ravi Ramamoorthi, Hao Su

In contrast, we propose adaptive thin volumes (ATVs); in an ATV, the depth hypothesis of each plane is spatially varying, which adapts to the uncertainties of previous per-pixel depth predictions.

3D Reconstruction Point Clouds

Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA

no code implementations4 Oct 2018 Cheng Fu, Shilin Zhu, Hao Su, Ching-En Lee, Jishen Zhao

Thus there does exist redundancy that can be exploited to further reduce the amount of on-chip computations.

Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?

1 code implementation CVPR 2019 Shilin Zhu, Xin Dong, Hao Su

Binary neural networks (BNN) have been studied extensively since they run dramatically faster at lower memory and power consumption than floating-point networks, thanks to the efficiency of bit operations.

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