3 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CV2021★ 3 cited
End-to-End Adaptive Monte Carlo Denoising and Super-Resolution
Xinyue Wei, Haozhi Huang, Yujin Shi +3
The classic Monte Carlo path tracing can achieve high quality rendering at the cost of heavy computation. Recent works make use of deep neural networks to accelerate this process,…
cs.LG2021★ 3 cited
Partial Graph Reasoning for Neural Network Regularization
Tiange Xiang, Chaoyi Zhang, Yang Song +3
Regularizers help deep neural networks prevent feature co-adaptations. Dropout, as a commonly used regularization technique, stochastically disables neuron activations during netwo…
cs.CV2021
Two-Stage Monte Carlo Denoising with Adaptive Sampling and Kernel Pool
Tiange Xiang, Hongliang Yuan, Haozhi Huang +1
Monte Carlo path tracer renders noisy image sequences at low sampling counts. Although great progress has been made on denoising such sequences, existing methods still suffer from…