7 papers · 1 filter
GeGS-PCR: Effective and Robust 3D Point Cloud Registration with Two-Stage Color-Enhanced Geometric-3DGS Fusion
Jiayi Tian, Haiduo Huang, Tian Xia +2
We address the challenge of point cloud registration using color information, where traditional methods relying solely on geometric features often struggle in low-overlap and incom…
SpecVLM: Fast Speculative Decoding in Vision-Language Models
Haiduo Huang, Fuwei Yang, Zhenhua Liu +4
Speculative decoding is a powerful way to accelerate autoregressive large language models (LLMs), but directly porting it to vision-language models (VLMs) faces unique systems cons…
DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer
Haiduo Huang, Jiangcheng Song, Yadong Zhang +1
Recent advances in knowledge distillation have emphasized the importance of decoupling different knowledge components. While existing methods utilize momentum mechanisms to separat…
Partial Convolution Meets Visual Attention
Haiduo Huang, Fuwei Yang, Dong Li +5
Designing an efficient and effective neural network has remained a prominent topic in computer vision research. Depthwise onvolution (DWConv) is widely used in efficient CNNs or Vi…
KernelDNA: Dynamic Kernel Sharing via Decoupled Naive Adapters
Haiduo Huang, Yadong Zhang, Yinghui Xu +1
Dynamic convolution enhances model capacity by adaptively combining multiple kernels, yet faces critical trade-offs: prior works either (1) incur significant parameter overhead by…
Partial Channel Network: Compute Fewer, Perform Better
Haiduo Huang, Tian Xia, Wenzhe zhao +1
Designing a module or mechanism that enables a network to maintain low parameters and FLOPs without sacrificing accuracy and throughput remains a challenge. To address this challen…
Nearly Lossless Adaptive Bit Switching
Haiduo Huang, Zhenhua Liu, Tian Xia +2
Model quantization is widely applied for compressing and accelerating deep neural networks (DNNs). However, conventional Quantization-Aware Training (QAT) focuses on training DNNs…