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cs.CV2025
Depth-Copy-Paste: Multimodal and Depth-Aware Compositing for Robust Face Detection
Qiushi Guo
Data augmentation is crucial for improving the robustness of face detection systems, especially under challenging conditions such as occlusion, illumination variation, and complex…
cs.LG2025
From Competition to Synergy: Unlocking Reinforcement Learning for Subject-Driven Image Generation
Ziwei Huang, Ying Shu, Hao Fang +5
Subject-driven image generation models face a fundamental trade-off between identity preservation (fidelity) and prompt adherence (editability). While online reinforcement learning…
cs.CV2025★ 1 cited
SynRailObs: A Synthetic Dataset for Obstacle Detection in Railway Scenarios
Qiushi Guo, Jason Rambach
Detecting potential obstacles in railway environments is critical for preventing serious accidents. Identifying a broad range of obstacle categories under complex conditions requir…