8 papers
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…
EGSRAL: An Enhanced 3D Gaussian Splatting based Renderer with Automated Labeling for Large-Scale Driving Scene
Yixiong Huo, Guangfeng Jiang, Hongyang Wei +9
3D Gaussian Splatting (3D GS) has gained popularity due to its faster rendering speed and high-quality novel view synthesis. Some researchers have explored using 3D GS for reconstr…
FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing
Zekai Li, Jintu Zheng, Ji Liu +9
Recently, large language models (LLMs) have demonstrated superior performance across various tasks by adhering to scaling laws, which significantly increase model size. However, th…
Fast Occupancy Network
Mingjie Lu, Yuanxian Huang, Ji Liu +5
Occupancy Network has recently attracted much attention in autonomous driving. Instead of monocular 3D detection and recent bird's eye view(BEV) models predicting 3D bounding box o…
VIPS-Odom: Visual-Inertial Odometry Tightly-coupled with Parking Slots for Autonomous Parking
Xuefeng Jiang, Fangyuan Wang, Rongzhang Zheng +5
Precise localization is of great importance for autonomous parking task since it provides service for the downstream planning and control modules, which significantly affects the s…
Amphista: Bi-directional Multi-head Decoding for Accelerating LLM Inference
Zeping Li, Xinlong Yang, Ziheng Gao +7
Large Language Models (LLMs) inherently use autoregressive decoding, which lacks parallelism in inference and results in significantly slow inference speed. While methods such as M…