3 citations · 3 across the 2 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
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…