TimeColor: Flexible Reference Colorization via Temporal Concatenation
Most colorization models condition only on a single reference, typically the first frame of the scene. However, this approach ignores other sources of conditional data, such as character sheets, background images, or arbitrary colorized frames. We propose TimeColor, a sketch-based video colorization model that supports heterogeneous, variable-count references with the use of explicit per-reference region assignment. TimeColor encodes references as additional latent frames which are concatenated temporally, permitting them to be processed concurrently in each diffusion step while keeping the model's parameter count fixed. TimeColor also uses spatiotemporal correspondence-masked attention to enforce subject -- reference binding in addition to modality-disjoint RoPE indexing. These mechanisms mitigate shortcutting and cross-identity palette leakage. Experiments on Sakuga-42M under both single- and multi-reference protocols show that TimeColor improves color fidelity, identity consistency, and temporal stability over prior baselines. Our project page is available at https://bconstantine.github.io/TimeColor/.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
OmniColor: A Unified Framework for Multi-modal Lineart Colorization
Lineart colorization is a critical stage in professional content creation, yet achieving precise and flexible results under diverse user constraints remains a significant challenge. To address this, we propose OmniColor,…
Temporal Consistent Automatic Video Colorization via Semantic Correspondence
Video colorization task has recently attracted wide attention. Recent methods mainly work on the temporal consistency in adjacent frames or frames with small interval. However, it still faces severe challenge of the inco…
ColorizationImage ColorizationSemantic correspondenceCobra: Efficient Line Art COlorization with BRoAder References
The comic production industry requires reference-based line art colorization with high accuracy, efficiency, contextual consistency, and flexible control. A comic page often involves diverse characters, objects, and back…
ColorizationImage GenerationLine Art ColorizationDeep Exemplar-based Video Colorization
This paper presents the first end-to-end network for exemplar-based video colorization. The main challenge is to achieve temporal consistency while remaining faithful to the reference style. To address this issue, we int…
ColorizationSemantic correspondenceVideo Colorization with Pre-trained Text-to-Image Diffusion Models
Video colorization is a challenging task that involves inferring plausible and temporally consistent colors for grayscale frames. In this paper, we present ColorDiffuser, an adaptation of a pre-trained text-to-image late…
Colorization