6 accepted papers
Panoramic semantic segmentation is pivotal for comprehensive 360deg scene understanding in critical applications like autonomous driving and virtual reality. However, progress in this domain is constrained by two key challenges: the severe geometric distortions inherent in panoramic projections and
Spiking neural networks (SNNs) promise energy-efficient inference, yet on static vision benchmarks they often trail matched ANNs under short simulation horizons. Under a matched-backbone and matched-budget protocol without extra tricks, we find that this ANN-SNN accuracy gap is consistently smaller …
Spiking Neural Networks (SNNs) offer promising energy efficiency and temporal sparsity for edge intelligence, but their training remains difficult due to gradient mismatch, membrane potential drift, and discretization errors. In this paper, we propose a membrane potential-guided surrogate optimizati
Text-rich images are ubiquitous in real-world applications, serving as a critical medium for conveying complex information and facilitating accessibility.Despite recent advances driven by Multimodal Large Language Models (MLLMs), existing benchmarks suffer from limited scale, fragmented scenarios, a
"∗ Equal contribution Corresponding authorIn this paper, we explore a novel framework, EGIInet (Explicitly Guided Information Interaction Network), a model for View-guided Point cloud Completion (ViPC) task, which aims to restore a complete point cloud from a partial one with a single view image. In…
Unpaired 3D object completion aims to predict a complete 3D shape from an incomplete input without knowing the correspondence between the complete and incomplete shapes. In this paper, we propose the novel KTNet to solve this task from the new perspective of knowledge transfer. KTNet elaborates a te…