6 papers · 1 filter
ProCrop: Learning Aesthetic Image Cropping from Professional Compositions
Ke Zhang, Tianyu Ding, Jiachen Jiang +4
Image cropping is crucial for enhancing the visual appeal and narrative impact of photographs, yet existing rule-based and data-driven approaches often lack diversity or require an…
CaesarNeRF: Calibrated Semantic Representation for Few-shot Generalizable Neural Rendering
Haidong Zhu, Tianyu Ding, Tianyi Chen +3
Generalizability and few-shot learning are key challenges in Neural Radiance Fields (NeRF), often due to the lack of a holistic understanding in pixel-level rendering. We introduce…
FORA: Fast-Forward Caching in Diffusion Transformer Acceleration
Pratheba Selvaraju, Tianyu Ding, Tianyi Chen +2
Diffusion transformers (DiT) have become the de facto choice for generating high-quality images and videos, largely due to their scalability, which enables the construction of larg…
AdaContour: Adaptive Contour Descriptor with Hierarchical Representation
Tianyu Ding, Jinxin Zhou, Tianyi Chen +3
Existing angle-based contour descriptors suffer from lossy representation for non-starconvex shapes. By and large, this is the result of the shape being registered with a single gl…
S3Editor: A Sparse Semantic-Disentangled Self-Training Framework for Face Video Editing
Guangzhi Wang, Tianyi Chen, Kamran Ghasedi +6
Face attribute editing plays a pivotal role in various applications. However, existing methods encounter challenges in achieving high-quality results while preserving identity, edi…
DREAM: Diffusion Rectification and Estimation-Adaptive Models
Jinxin Zhou, Tianyu Ding, Tianyi Chen +4
We present DREAM, a novel training framework representing Diffusion Rectification and Estimation Adaptive Models, requiring minimal code changes (just three lines) yet significantl…