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20242026
most citedDuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation

6 citations · 13 across the 17 of their papers we have counts for

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cs.CV2026

Video-MSR: Benchmarking Multi-hop Spatial Reasoning Capabilities of MLLMs

Rui Zhu, Xin Shen, Shuchen Wu +6

Spatial reasoning has emerged as a critical capability for Multimodal Large Language Models (MLLMs), drawing increasing attention and rapid advancement. However, existing benchmark…

cs.CV2025

FingerCap: Fine-grained Finger-level Hand Motion Captioning

Xin Shen, Rui Zhu, Lei Shen +10

Understanding fine-grained human hand motion is fundamental to visual perception, embodied intelligence, and multimodal communication. In this work, we propose Fine-grained Finger-…

cs.CV2025

Facial-R1: Aligning Reasoning and Recognition for Facial Emotion Analysis

Jiulong Wu, Yucheng Shen, Lingyong Yan +4

Facial Emotion Analysis (FEA) extends traditional facial emotion recognition by incorporating explainable, fine-grained reasoning. The task integrates three subtasks: emotion recog…

cs.CV20254 cited

LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating

Deguo Xia, Weiming Zhang, Xiyan Liu +6

An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience of autonomous driving systems.…

cs.CV20246 cited

DuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation

Deguo Xia, Weiming Zhang, Xiyan Liu +5

Generating city-scale lane-level maps faces significant challenges due to the intricate urban environments, such as blurred or absent lane markings. Additionally, a standard lane-l…