collaborators

8 papers

cs.CV2026

CrossEarth-Gate: Fisher-Guided Adaptive Tuning Engine for Efficient Adaptation of Cross-Domain Remote Sensing Semantic Segmentation

Shilei Cao, Ziyang Gong, Hehai Lin +10

In Remote Sensing (RS), Parameter-Efficient Fine-Tuning (PEFT) has emerged as a key approach to activate the generalizable representation ability of foundation models for downstrea…

cs.AI2026

Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?

Fei Lin, Ziyang Gong, Cong Wang +9

Toxicity remains a leading cause of early-stage drug development failure. Despite advances in molecular design and property prediction, the task of molecular toxicity repair, gener…

cs.CV2026

Object Fidelity Diffusion for Remote Sensing Image Generation

Ziqi Ye, Shuran Ma, Jie Yang +5

High-precision controllable remote sensing image generation is both meaningful and challenging. Existing diffusion models often produce low-fidelity images due to their inability t…

cs.CV2026

GeneMAN: Generalizable Single-Image 3D Human Reconstruction from Multi-Source Human Data

Wentao Wang, Hang Ye, Fangzhou Hong +5

Given a single in-the-wild human photo, it remains a challenging task to reconstruct a high-fidelity 3D human model. Existing methods face difficulties including a) the varying bod…

cs.CV2025

Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency Adaptation

Xiaoxing Hu, Ziyang Gong, Yupei Wang +8

Parameter-Efficient Fine-Tuning (PEFT) is a technique that allows us to adapt powerful Foundation Models (FMs) to diverse downstream tasks while preserving and unleashing their inh…

cs.CV2025

SpaCE-10: A Comprehensive Benchmark for Multimodal Large Language Models in Compositional Spatial Intelligence

Ziyang Gong, Wenhao Li, Oliver Ma +7

Multimodal Large Language Models (MLLMs) have achieved remarkable progress in various multimodal tasks. To pursue higher intelligence in space, MLLMs require integrating multiple s…