3 accepted papers
The nonlinear two-time-scale stochastic approximation is widely studied under conditions of bounded variances in noise. Motivated by recent advances that allow for variability linked to the current state or time, we consider state- and time-dependent noises. We show that the Lyapunov function exhibi…
Calibration-based methods have dominated RAW image denoising under extremely low-light environments. However, these methods suffer from several main deficiencies: 1) the calibration procedure is laborious and time-consuming, 2) denoisers for different cameras are difficult to transfer, and 3) the di…
Bounding box regression is a very effective method to improve the localization accuracy of object detection. Recently, the IoU-based regression losses have been widely used in object detection algorithms. However, we observe that they degenerate seriously in the late training period, leading to slow…