关注领域：

AIGC

3D computer vision learning

(相关资料图)

Fine-grained learning

GNN

其他

声明

论文较多，时间有限，本专栏无法做文章的讲解，只挑选出符合PaperABC研究兴趣和当前热点问题相关的论文，如果你的research topic和上述内容有关，那本专栏可作为你的论文更新源或Paper reading list．

Paper list:

AIGC:

1. Composer: Creative and Controllable Image Synthesis with Composable Conditions

2. Learning 3D Photography Videos via Self-supervised Diffusion on Single Images

3. 3D-aware Conditional Image Synthesis

4. Text-driven Visual Synthesis with Latent Diffusion Prior

5. LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation

6. Learning 3D Photography Videos via Self-supervised Diffusion on Single Images

7. On Calibrating Diffusion Probabilistic Models

细粒度学习：

1. Semantic Feature Integration network forFine-grained Visual Classification

3D 视觉：

1. MVFusion: Multi-View 3D Object Detection with Semantic-alignedRadar and Camera Fusion

2. Few-Shot Point Cloud Semantic Segmentation viaContrastive Self-Supervision and Multi-Resolution Attention

3. USR: Unsupervised Separated 3D Garment and Human Reconstruction viaGeometry and Semantic Consistency

4. MonoPGC: Monocular 3D Object Detection withPixel Geometry Contexts

5. RealFusion360◦ Reconstruction of Any Object from a Single Image

6. PC2: Projection-Conditioned Point CloudDiffusion for Single-Image 3D Reconstruction 

自监督学习：

1. Self-supervised learning of Split Invariant Equivariant representations

关键词： 监督学习