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DreamSparse: Escaping from Plato's Cave with 2D Frozen Diffusion Model Given Sparse Views
Paul Yoo, Jiaxian Guo, Yutaka Matsuo +1
Synthesizing novel view images from a few views is a challenging but practical problem. Existing methods often struggle with producing high-quality results or necessitate per-objec…
Paste, Inpaint and Harmonize via Denoising: Subject-Driven Image Editing with Pre-Trained Diffusion Model
Xin Zhang, Jiaxian Guo, Paul Yoo +2
Text-to-image generative models have attracted rising attention for flexible image editing via user-specified descriptions. However, text descriptions alone are not enough to elabo…
Realtime Data-Efficient Portrait Stylization Based On Geometric Alignment
Xinrui Wang, Zhuoru Li, Xiao Zhou +2
Portrait Stylization aims to imbue portrait photos with vivid artistic effects drawn from style examples. Despite the availability of enormous training datasets and large network w…
Deep Billboards towards Lossless Real2Sim in Virtual Reality
Naruya Kondo, So Kuroki, Ryosuke Hyakuta +3
An aspirational goal for virtual reality (VR) is to bring in a rich diversity of real world objects losslessly. Existing VR applications often convert objects into explicit 3D mode…
Robustifying Vision Transformer without Retraining from Scratch by Test-Time Class-Conditional Feature Alignment
Takeshi Kojima, Yutaka Matsuo, Yusuke Iwasawa
Vision Transformer (ViT) is becoming more popular in image processing. Specifically, we investigate the effectiveness of test-time adaptation (TTA) on ViT, a technique that has eme…
Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains
Xin Zhang, Shixiang Shane Gu, Yutaka Matsuo +1
Domain generalization (DG) is a difficult transfer learning problem aiming to learn a generalizable model for unseen domains. Recent foundation models (FMs) are robust to many dist…