3 papers
cs.CV2026
DrivePTS: A Progressive Learning Framework with Textual and Structural Enhancement for Driving Scene Generation
Zhechao Wang, Yiming Zeng, Lufan Ma +4
Synthesis of diverse driving scenes serves as a crucial data augmentation technique for validating the robustness and generalizability of autonomous driving systems. Current method…
cs.CV2022
UniInst: Unique Representation for End-to-End Instance Segmentation
Yimin Ou, Rui Yang, Lufan Ma +5
Existing instance segmentation methods have achieved impressive performance but still suffer from a common dilemma: redundant representations (e.g., multiple boxes, grids, and anch…
cs.CV2021
Implicit Feature Refinement for Instance Segmentation
Lufan Ma, Tiancai Wang, Bin Dong +3
We propose a novel implicit feature refinement module for high-quality instance segmentation. Existing image/video instance segmentation methods rely on explicitly stacked convolut…