The paper presents CaloPointFlow II, a new generative model for simulating calorimeter showers as point clouds. This model improves upon its predecessor by introducing CDF-Dequantization and DeepSetFlow, which enhance the accuracy and efficiency of calorimeter simulations. The model is evaluated using the Fast Calorimeter Simulation Challenge (CaloChallenge) datasets II and III. The CDF-Dequantization technique addresses the issue of dequantization by mapping discrete distributions to normal distributions, while DeepSetFlow enables modeling of point-to-point correlations. The model also incorporates a rotational symmetry approach to mitigate the "multiple hit" problem, which arises when multiple points are generated within a single calorimeter cell. The model's performance is compared to traditional simulation methods like GEANT4, showing improved accuracy and efficiency in simulating calorimeter showers. The results demonstrate that CaloPointFlow II achieves high accuracy in simulating the energy distribution, spatial structure, and correlations within calorimeter showers, making it a promising tool for high-energy physics experiments. The model's efficiency and accuracy make it suitable for large-scale simulations, which are increasingly necessary due to the high luminosity of future experiments. The paper concludes that CaloPointFlow II represents a significant advancement in the simulation of calorimeter showers, offering a computationally efficient and accurate alternative to traditional methods.The paper presents CaloPointFlow II, a new generative model for simulating calorimeter showers as point clouds. This model improves upon its predecessor by introducing CDF-Dequantization and DeepSetFlow, which enhance the accuracy and efficiency of calorimeter simulations. The model is evaluated using the Fast Calorimeter Simulation Challenge (CaloChallenge) datasets II and III. The CDF-Dequantization technique addresses the issue of dequantization by mapping discrete distributions to normal distributions, while DeepSetFlow enables modeling of point-to-point correlations. The model also incorporates a rotational symmetry approach to mitigate the "multiple hit" problem, which arises when multiple points are generated within a single calorimeter cell. The model's performance is compared to traditional simulation methods like GEANT4, showing improved accuracy and efficiency in simulating calorimeter showers. The results demonstrate that CaloPointFlow II achieves high accuracy in simulating the energy distribution, spatial structure, and correlations within calorimeter showers, making it a promising tool for high-energy physics experiments. The model's efficiency and accuracy make it suitable for large-scale simulations, which are increasingly necessary due to the high luminosity of future experiments. The paper concludes that CaloPointFlow II represents a significant advancement in the simulation of calorimeter showers, offering a computationally efficient and accurate alternative to traditional methods.