6 papers
Adversarial Attacks Already Tell the Answer: Directional Bias-Guided Test-time Defense for Vision-Language Models
Liangsheng Liu, Si Chen, Jiamin Wu +5
Vision-Language Models (VLMs), such as CLIP, have shown strong zero-shot generalization but remain highly vulnerable to adversarial perturbations, posing serious risks in real-worl…
FS-I2P:A Hierarchical Focus-Sweep Registration Network with Dynamically Allocated Depth
Zhixin Cheng, Yujia Chen, Xujing Tao +4
Image-to-point cloud registration is often challenged by viewpoint changes, cross-modal discrepancies, and repetitive textures, which induce scale ambiguity and consequently lead t…
GLASS: Geometry-aware Local Alignment and Structure Synchronization Network for 2D-3D Registration
Zhixin Cheng, Jiacheng Deng, Xinjun Li +5
Image-to-point cloud registration methods typically follow a coarse-to-fine pipeline, extracting patch-level correspondences and refining them into dense pixel-to-point matches. Ho…
VCR: Variance-Driven Channel Recalibration for Robust Low-Light Enhancement
Zhixin Cheng, Fangwen Zhang, Xiaotian Yin +2
Most sRGB-based LLIE methods suffer from entangled luminance and color, while the HSV color space offers insufficient decoupling at the cost of introducing significant red and blac…
Adaptive Agent Selection and Interaction Network for Image-to-point cloud Registration
Zhixin Cheng, Xiaotian Yin, Jiacheng Deng +5
Typical detection-free methods for image-to-point cloud registration leverage transformer-based architectures to aggregate cross-modal features and establish correspondences. Howev…
CA-I2P: Channel-Adaptive Registration Network with Global Optimal Selection
Zhixin Cheng, Jiacheng Deng, Xinjun Li +5
Detection-free methods typically follow a coarse-to-fine pipeline, extracting image and point cloud features for patch-level matching and refining dense pixel-to-point corresponden…