Sharing a ComfyUI workflow for image-to-video generation. This is an adapted and slightly modified version of a workflow originally created by an acquaintance.
It utilizes a two-pass KSampler system, focusing on LoRAs effective at low step counts, with a particular emphasis on CausVid for refinement.
Independent LoRA for Each Pass (User Customization):
Feature: You can apply separate sets of LoRAs to the 1st (initial generation) and 2nd (refinement) KSampler passes.
Advantage: This gives you granular control. For instance, use foundational LoRAs in the first pass and specialized motion/detail LoRAs (like CausVid) in the second, or experiment with completely different combinations as you see fit.
Addresses Common CausVid LoRA Challenges & Enhances Low-Step Performance:
Problem Solved: Directly tackles issues sometimes seen with CausVid LoRA (and other low-step focused LoRAs) where motion can be weak or artifacts appear when generating with very few steps in a single pass.
How it Improves:
The 1st pass quickly establishes a coherent base latent, even at minimal steps (e.g., 2-5).
The 2nd pass then leverages CausVid (and other LoRAs) on this pre-generated latent. This targeted refinement at low steps (e.g., 4-12, with CFG around 1.0) allows CausVid to perform optimally, enhancing motion and cleaning up potential issues more effectively than a single, rushed low-step generation.
Advantage: You get the speed benefits of low steps while mitigating common quality/motion degradation, leading to better, more consistent results with efficient LoRAs like CausVid.
This structured, two-stage process allows for more robust and refined outputs, especially when pushing for speed with very low step counts and relying on powerful efficiency LoRAs.
Custom Nodes
https://github.com/pythongosssss/ComfyUI-Custom-Scripts
https://github.com/ltdrdata/ComfyUI-Impact-Pack
https://github.com/yolain/ComfyUI-Easy-Use
https://github.com/WASasquatch/was-node-suite-comfyui
https://github.com/kijai/ComfyUI-KJNodes
https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite
https://github.com/Fannovel16/ComfyUI-Frame-Interpolation
https://github.com/ltdrdata/ComfyUI-Inspire-Pack
Description
[V1.1]
VRAM Optimization: Partially resolved issues with excessive VRAM consumption, leading to more stable and efficient operation in some scenarios.
Node update: Updated internal nodes to their latest versions from kjnodes for better performance and compatibility.
ComfyUI Update Required: To ensure full compatibility and take advantage of these changes, please update your ComfyUI installation to the latest version before using this updated workflow.