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@article{201707,
        author = {Prem Iche},
        title = {Research On IMPLEMENTATION OF COMFYUI IN THE VFX PAINT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {5774-5778},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201707},
        abstract = {The integration of Artificial Intelligence (AI) into the Visual Effects (VFX) industry has significantly transformed traditional workflows, particularly in paint and clean-up tasks. ComfyUI, a node-based AI interface, enables artists to automate processes such as object removal, clean plate generation, and texture reconstruction. While these advancements promise improved efficiency and reduced manual workload, they also introduce challenges related to workflow complexity, cognitive load, and decision fatigue. This study investigates the implementation of ComfyUI in the VFX paint industry using a secondary research methodology. Drawing from literature in VFX pipelines, human-computer interaction, and cognitive load theory, the research identifies how AI tools impact artist performance and decision-making. The findings reveal that although ComfyUI enhances speed and automation, excessive node complexity and multiple AI outputs increase cognitive burden. To address these challenges, the paper proposes the PACE-VFX Framework, consisting of Progressive Node Disclosure, Adaptive Workflow Hierarchy, Contextual Tool Surfacing, and Embedded Cognitive Rest. This framework provides practical guidelines for integrating AI tools effectively into VFX workflows.},
        keywords = {ComfyUI, Cognitive Load, VFX Paint Industry, AI Workflow, PACE-VFX Framework, Decision Fatigue, Node-Based Pipelines, Automation},
        month = {May},
        }