6 accepted papers
The rapid advancement of educational applications, artistic creation, and AI-generated content (AIGC) technologies has substantially increased practical requirements for comprehensive Image Aesthetics Assessment (IAA), particularly demanding methods capable of delivering both quantitative scoring an
Video understanding requires identifying and reasoning over semantically discriminative visual objects across frames, yet existing object-agnostic solutions struggle to effectively handle substantial object variations over time. To address this, we introduce Chain-of-Glimpse, a search-guided progres…
LiDAR semantic segmentation is a key task in advanced autonomous driving systems. Projection-based methods exhibit real-time potential due to their efficiency, but suffer from inevitable 3D information loss and rely on time-consuming post-processing, limiting overall performance. To address this, we
Myocardial infarction (MI) is one of the most dangerous cardiovascular diseases, typically diagnosed using electrocardiogram (ECG). While many deep learning methods exist for MI detection, they often overlook the correlations and medical knowledge between leads of ECG, resulting in limited interpret…
To address the limitations inherent to conventional automated harvesting robots specifically their suboptimal success rates and risk of crop damage, we design a novel bot named AHPPEBot which is capable of autonomous harvesting based on crop phenotyping and pose estimation. Specifically, In phenotyp…
Cross-modality point cloud registration is confronted with significant challenges due to inherent differences in modalities between sensors. To deal with this problem, we propose FF-LOGO: a cross-modality point cloud registration framework with Feature Filtering and LOcal-Global Optimization. The cr…