AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario

no code implementations • 28 May 2024 • Yuhan Li, Hao Zhou, Wenxiang Shang, Ran Lin, Xuanhong Chen, Bingbing Ni

While image-based virtual try-on has made significant strides, emerging approaches still fall short of delivering high-fidelity and robust fitting images across various scenarios, as their models suffer from issues of ill-fitted garment styles and quality degrading during the training process, not to mention the lack of support for various combinations of attire.

Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models

1 code implementation • 3 Apr 2024 • Haoran Sun, Lixin Liu, Junjie Li, Fengyu Wang, Baohua Dong, Ran Lin, Ruohui Huang

To address this challenge, we introduce Conifer, a novel instruction tuning dataset, designed to enhance LLMs to follow multi-level instructions with complex constraints.

Instruction Following