From the 1 of 7 linked papers with an AI index.
7 papers
Long-Tailed 3D Point Cloud Dataset Distillation
Jiahao You, Xu Han, Jinfeng Xu +1
The paper introduces a method for distilling large 3D point‑cloud datasets into compact synthetic sets while explicitly handling long‑tailed class distributions, using adaptive syn…
Efficient RWKV-based Representation Learning for 3D Point Clouds
Yun Liu, Xuefeng Yan, Liangliang Nan +5
The recent receptance weighted key value (RWKV) model combines RNN-style recurrence, offering a linear-complexity alternative to Transformers' quadratic self-attention for modeling…
Towards Pixel-Wise Anomaly Location for High-Resolution PCBA via Self-Supervised Image Reconstruction
Wuyi Liu, Le Jin, Junxian Yang +5
Automated defect inspection of assembled Printed Circuit Board Assemblies (PCBA) is quite challenging due to the insufficient labeled data, micro-defects with just a few pixels in…
LumiX: Structured and Coherent Text-to-Intrinsic Generation
Xu Han, Biao Zhang, Xiangjun Tang +2
We present LumiX, a structured diffusion framework for coherent text-to-intrinsic generation. Conditioned on text prompts, LumiX jointly generates a comprehensive set of intrinsic…
MoST: Efficient Monarch Sparse Tuning for 3D Representation Learning
Xu Han, Yuan Tang, Jinfeng Xu +1
We introduce Monarch Sparse Tuning (MoST), the first reparameterization-based parameter-efficient fine-tuning (PEFT) method tailored for 3D representation learning. Unlike existing…
Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model
Xu Han, Yuan Tang, Zhaoxuan Wang +1
Existing Transformer-based models for point cloud analysis suffer from quadratic complexity, leading to compromised point cloud resolution and information loss. In contrast, the ne…