Greatness in Simplicity: Unified Self-Cycle Consistency for Parser-Free Virtual Try-On Junyin Wang
–Neural Information Processing Systems
Image-based virtual try-on tasks remain challenging, primarily due to inherent complexities associated with non-rigid garment deformation modeling and strong feature entanglement of clothing within human body. Recent groundbreaking formulations, such as in-painting, cycle consistency, and knowledge distillation, have facilitated self-supervised generation of try-on images.
Neural Information Processing Systems
Feb-7-2025, 08:20:49 GMT
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- Research Report (0.46)