Poster "subject-driven generation" Papers

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ArtiFade: Learning to Generate High-quality Subject from Blemished Images

Shuya Yang, Shaozhe Hao, Yukang Cao et al.

CVPR 2025arXiv:2409.03745

Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator

Chaehun Shin, Jooyoung Choi, Heeseung Kim et al.

CVPR 2025arXiv:2411.15466

Track, Inpaint, Resplat: Subject-driven 3D and 4D Generation with Progressive Texture Infilling

Shuhong Zheng, Ashkan Mirzaei, Igor Gilitschenski

NEURIPS 2025arXiv:2510.23605

Transformed Low-rank Adaptation via Tensor Decomposition and Its Applications to Text-to-image Models

Zerui Tao, Yuhta Takida, Naoki Murata et al.

ICCV 2025arXiv:2501.08727

UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal Transformer for Image Generation

Lunhao Duan, Shanshan Zhao, Wenjun Yan et al.

CVPR 2025arXiv:2412.18928

UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer

Haoxuan Wang, Jinlong Peng, Qingdong He et al.

ICCV 2025arXiv:2503.09277

ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAs

Viraj Shah, Nataniel Ruiz, Forrester Cole et al.

ECCV 2024arXiv:2311.13600