activity
20242026
most citedAdvancing the Understanding of Fine-Grained 3D Forest Structures using Digital Cousins and Simulation-to-Reality: Methods and Datasets

2 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

ForestHG-Trace: Traceable Long-Horizon Ecological Reasoning over Large-Scale Forest Scenes

Zihang Cheng, Duanchu Wang, Cheng Li +3

Remote sensing question answering (RS-QA) often requires more than direct semantic prediction, especially in large-scale forest scenes where ecological analysis involves multi-step…

cs.CV2026

PointQ-Bench: Benchmarking Diagnostic and Interpretable Point Cloud Quality Assessment

Duanchu Wang, Cheng Li, Junjie Yang +5

Point cloud quality plays a critical role in 3D acquisition, reconstruction, rendering, and perception, yet existing point cloud quality assessment (PCQA) research remains largely…

cs.CV2026

Beyond Appearance: Can Multimodal Large Language Models Exploit Vertical Structure for Remote Sensing Natural Scene Understanding?

Jing Huang, Duanchu Wang, Junjie Yang +5

Multimodal large language models (MLLMs) have advanced rapidly in remote-sensing analysis, yet existing evaluations remain predominantly 2D-centric. Because spectrally confused reg…

cs.CV20252 cited

Advancing the Understanding of Fine-Grained 3D Forest Structures using Digital Cousins and Simulation-to-Reality: Methods and Datasets

Jing Liu, Duanchu Wang, Haoran Gong +3

Understanding and analyzing the spatial semantics and structure of forests is essential for accurate forest resource monitoring and ecosystem research. However, the lack of large-s…

cs.CV20242 cited

CompetitorFormer: Competitor Transformer for 3D Instance Segmentation

Duanchu Wang, Jing Liu, Haoran Gong +2

Transformer-based methods have become the dominant approach for 3D instance segmentation. These methods predict instance masks via instance queries, ranking them by classification…