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From the 1 of 18 linked papers with an AI index.

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20242026
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cs.CV2026

LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection

Wenhao Dong, Xiaoyan Luo, Linlin Yang +4

The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing methods prefer dual-stream CNN bac…

cs.CV2026

InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection

Zichao Feng, Haodong Zhu, Jingying Yang +8

Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based methods typically require both R…

cs.CV2026

Teaching Vision-Language-Action Models What to See and Where to Look

Yuguang Yang, Canyu Chen, Zhewen Tan +10

Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing VLAs' training relies heavily on text-centric visual q…

cs.CV2026

CL-CLIP: CLIP-Based Continual Learning Framework with Cost-Volume Category Decoupling for Object Detection

Zihan Liu, Yuguang Yang, Shengjie Su +5

Continual Object Detection (COD) requires a detector to acquire new categories over time while preserving previously learned ones. This goal is closely related to open-vocabulary d…

cs.CV2026

Devil is in Narrow Policy: Unleashing Exploration in Driving VLA Models

Canyu Chen, Yuguang Yang, Zhewen Tan +10

We identify a fundamental Narrow Policy limitation undermining the performance of autonomous VLA models, where driving Imitation Learning (IL) tends to collapse exploration and lim…

cs.CV2026

UrbanGS: A Scalable and Efficient Architecture for Geometrically Accurate Large-Scene Reconstruction

Changbai Li, Haodong Zhu, Hanlin Chen +6

While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges i…