✍️ Text Generation

📷 CVPR2025 · 2 paper notes

📌 Same area in other venues: 🔬 ICLR2026 (12) · 💬 ACL2026 (17) · 🧪 ICML2026 (2) · 🤖 AAAI2026 (3) · 📹 ICCV2025 (1) · 🧪 ICML2025 (1)

ArtFormer: Controllable Generation of Diverse 3D Articulated Objects

This work proposes the ArtFormer framework, which generates high-quality, diverse, and kinematically accurate 3D articulated objects from text/image descriptions via tree structure parameterization and a conditional diffusion shape prior, significantly outperforming existing methods in generation quality and diversity.

Dense Match Summarization for Faster Two-view Estimation

This paper proposes a dense match summarization scheme that compresses over 10,000 dense matches into approximately 1% representative matches through clustering and representative match selection. It encodes the geometric constraints of each cluster into a 9×9 matrix, achieving a 10× to 100× speedup for robust RANSAC estimation with negligible accuracy loss.