most citedMSWA: Refining Local Attention with Multi-ScaleWindow Attention

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cs.CV2025

DL-QAT: Weight-Decomposed Low-Rank Quantization-Aware Training for Large Language Models

Wenjin Ke, Zhe Li, Dong Li +2

Improving the efficiency of inference in Large Language Models (LLMs) is a critical area of research. Post-training Quantization (PTQ) is a popular technique, but it often faces ch…

cs.CV2025

MonoGS++: Fast and Accurate Monocular RGB Gaussian SLAM

Renwu Li, Wenjing Ke, Dong Li +2

We present MonoGS++, a novel fast and accurate Simultaneous Localization and Mapping (SLAM) method that leverages 3D Gaussian representations and operates solely on RGB inputs. Whi…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization

Haowei Zhu, Dehua Tang, Ji Liu +12

Diffusion models have achieved remarkable progress in the field of image generation due to their outstanding capabilities. However, these models require substantial computing resou…