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ComfyUI Video Anti-Aliasing Pack

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Advanced anti-aliasing nodes for videos and images. VideoTAADLAA combines TAA with a DLAA-inspired pipeline for sharp, stable results, while VideoAdaptiveAA targets specific aliasing-prone regions. The system utilizes temporal accumulation, jittered sampling, and CNN-based refinement for superior edge quality.


Important

Disclaimer This node does not use NVIDIA's closed-source SDKs or native DLAA/DLSS binaries. Instead, it is a custom adaptation of Temporal and Spatial Anti-Aliasing techniques commonly found in modern game engines, rebuilt entirely from scratch using PyTorch tensor architecture specifically for ComfyUI video post-processing.


Preview

TAA + DLAA Anti-Aliasing Adaptive Anti-Aliasing
Video TAA + DLAA Node Video Adaptive AA Node

Features

  • Temporal Anti-Aliasing (TAA): Reduces flickering using frame history blending with motion-aware masking.
  • Neural Refinement (DLAA-style): Lightweight CNN residual enhancement inspired by DLAA-like reconstruction
  • Ghosting Reduction Logic: History clamping with motion-based alpha suppression to minimize trailing artifacts.
  • Fixed Pattern Jittering: Deterministic 4-offset sub-pixel jitter for improved sampling stability (not Halton).
  • Edge-Aware Weighting: Sobel edge detection for selective blurring to suppress aliasing while preserving details.
  • Selective Edge-Based Anti-Aliasing: Applies blur to high-gradient areas using edge threshold masks.

Comparison


AdaptiveAA Comparison


TAA + DLAA Comparison


🚀 How to use

  • Test the effect by increasing dlaa_strength to 0.8 or 1.0.
  • If you use it in videos with fast motion, try increasing motion_sensitivity or decreasing taa_alpha.

Parameters

  • taa_strength: Controls the impact of past frames. (Default: 0.6 | Fast motion: 0.7 | Static: 0.95)
  • taa_alpha: Determines how quickly history updates. (Default: 0.4 | Aggressive AA: 0.3 | Ghost-free: 0.05)
  • motion_sensitivity: For high-speed videos, try decreasing. (Default: 0.08 | Flicker-prone: 0.0 | Ghosting Risk: 0.3)
  • jitter_scale: Amount of sub-pixel shifting for edge detection. (Default: 0.02 | Off: 0.0 | Maximum: 0.08)
  • dlaa_strength: Strength of the deep learning sharpening. (Default: 0.3 | Pure AA: 0.0 | Aggressive: 1.0)
  • edge_threshold: Determines which pixels are detected as edges. (Default: 0.2 | Hard edges: 0.35 | All: 0.05)
  • blur_radius: The radius of the blur applied to edges. (Default: 0 | Softer: 2–3 | Very soft: 4–5)
  • reset_history: Clears temporal history memory. (Default: False | Enable on scene change: True)

Installation

Recommended: Install via ComfyUI-Manager.

Manual installation:

cd ComfyUI/custom_nodes/
git clone https://github.com/MSXYZ-GenAI/comfyui-msxyz.git

License

This project is licensed under the MIT License - see the LICENSE file for details.

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