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Wenlong Luo

3 accepted papers

2026

Incremental Object Detection via Future-Aware Decoupled Cross-Head Distillation

CVPR 2026

Incremental Object Detection (IOD) enables AI systems to continuously acquire new object classes while preserving knowledge of previously learned ones, an ability essential for deployment in dynamic, real-world environments. Existing IOD methods typically rely on knowledge distillation to mitigate c

Cited by 0SourceScholar
2025

Gradient Decomposition and Alignment for Incremental Object Detection

ICCV 2025poster

Incremental object detection (IOD) is crucial for enabling AI systems to continuously learn new object classes over time while retaining knowledge of previously learned categories, allowing model to adapt to dynamic environments without forgetting prior information.Existing IOD methods primarily emp…

2024

Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation Approach

ECCV 2024poster

"In this paper, we construct a large-scale benchmark dataset for Ground-to-Aerial Video-based person Re-Identification, named G2A-VReID, which comprises 185,907 images and 5,576 tracklets, featuring 2,788 distinct identities. To our knowledge, this is the first dataset for video ReID under Ground-to…