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Follow-Your-Color: Multi-Instance Sketch Colorization
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We present Follow-Your-Color, a diffusion-based framework for multi-instance sketch colorization. The production of multi-instance 2D line art colorization adheres to an industry-standard workflow, which consists of three crucial stages: the design of line art characters, the coloring of individual objects, and the refinement process. The artists are required to repeat the process of coloring each instance one by one, which is inaccurate and inefficient. Meanwhile, current generative methods fail to solve this task due to the challenge of multi-instance pair data collection. To tackle these challenges, we incorporate three technical designs to ensure precise character detail transcription and achieve multi-instance sketch colorization in a single forward pass. Specifically, we first propose the self-play training strategy to address the lack of training data. Then we introduce an instance guider to feed the color of the instance. To achieve accurate color matching, we present fine-grained color matching with edge loss to enhance visual quality. Equipped with the proposed modules, Follow-Your-Color enables automatically transforming sketches into vividly-colored images with accurate consistency and multi-instance control. Experiments on our collected datasets show that our model outperforms existing methods regarding chromatic precision. Specifically, our model critically automates the colorization process with zero manual adjustments, so novice users can produce stylistically consistent artwork by providing reference instances and the original line art. Our code and additional details are available at https://yinhan-zhang.github.io/color.
Forward citations
Cited by 7 Pith papers
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LongAnimation: Long Animation Generation with Dynamic Global-Local Memory
LongAnimation uses a dynamic global-local memory, built from a long-video-understanding model's KV cache, to colorize animation sequences of about 500 frames with stable color consistency.
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SketchColour: Channel Concat Guided DiT-based Sketch-to-Colour Pipeline for 2D Animation
SketchColour colors animation sketches from a single colored first frame by replacing the U-Net with a Diffusion Transformer, using channel-concat conditioning and LoRA fine-tuning.
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Follow-Your-Instruction: A Comprehensive MLLM Agent for World Data Synthesis
An MLLM-driven pipeline that composes 3D scenes from assets, optimizes them with multi-view VLM feedback, and renders videos, yielding synthetic data that modestly improves several 2D, 3D, and 4D generative baselines.
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Follow-Your-Creation: Empowering 4D Creation through Video Inpainting
Follow-Your-Creation fine-tunes the Wan2.1 video inpainting model on composite point-cloud and editing masks so a single monocular video can be converted into editable 4D video with new camera motion.
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SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping
SkipVAR selects, per sample, between step skipping and unconditional branch replacement using handcrafted frequency features and a trained logistic regression, to accelerate visual autoregressive generation.
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