UniCycleFlow: Bidirectional Unpaired Image Translation with a Shared Rectified Flow

• URL: http://arxiv.org/abs/2608.06784v1
• Date: Fri, 07 Aug 2026 04:05:04 GMT
• Title: UniCycleFlow: Bidirectional Unpaired Image Translation with a Shared Rectified Flow
• Abstract summary: Bidirectional unpaired image translation must preserve source-specific structure while learning coherent transformations in both directions without paired supervision.<n>We propose UniCycleFlow, a rectified-flow framework that represents bidirectional translation as forward and reverse integration of a single time-conditioned velocity field.
• Score: 14.60117153247222
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Bidirectional unpaired image translation must preserve source-specific structure while learning coherent transformations in both directions without paired supervision. Existing methods typically employ two direction-specific generators or train separate one-way models. Even when linked by cycle consistency, such models constrain only the round-trip endpoint reconstruction, without requiring the two directions to obey a common local transformation rule. We propose UniCycleFlow, a rectified-flow framework that represents bidirectional translation as forward and reverse integration of a single time-conditioned velocity field. This formulation organizes both directions within the same continuous dynamics, rather than coupling otherwise separate endpoint mappings. A key challenge is that unpaired data provide no meaningful source--target coupling from which rectified-flow trajectories can be constructed. UniCycleFlow addresses this challenge by learning deterministic source-conditioned endpoints whose marginal distributions are adversarially matched to the opposite domains. The resulting paths are regularized by stop-gradient self-flow matching for intermediate velocity supervision, discrete cycle closure for forward--reverse consistency, and representation path-velocity regularization for controlling localized feature changes along the trajectory. Across ten translation directions, UniCycleFlow achieves the lowest FID on 7 of 10 tasks using a single Euler evaluation and obtains the best average FID of 55.1.

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