most citedAutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.SE20251 cited

AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine

Shuyang Hou, Zhangxiao Shen, Huayi Wu +10

Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task…

cs.CV2025

Advancing Video Self-Supervised Learning via Image Foundation Models

Jingwei Wu, Zhewei Huang, Chang Liu

In the past decade, image foundation models (IFMs) have achieved unprecedented progress. However, the potential of directly using IFMs for video self-supervised representation lear…

cs.CV2025

Detection of Underwater Multi-Targets Based on Self-Supervised Learning and Deformable Path Aggregation Feature Pyramid Network

Chang Liu

To overcome the constraints of the underwater environment and improve the accuracy and robustness of underwater target detection models, this paper develops a specialized dataset f…

cs.CV2025

DiTPainter: Efficient Video Inpainting with Diffusion Transformers

Xian Wu, Chang Liu

Many existing video inpainting algorithms utilize optical flows to construct the corresponding maps and then propagate pixels from adjacent frames to missing areas by mapping. Desp…

cs.CV2024

Make Your Actor Talk: Generalizable and High-Fidelity Lip Sync with Motion and Appearance Disentanglement

Runyi Yu, Tianyu He, Ailing Zhang +6

We aim to edit the lip movements in talking video according to the given speech while preserving the personal identity and visual details. The task can be decomposed into two sub-p…