8 accepted papers
Industrial visual inspection is crucial for detecting defects in manufactured products, but it traditionally relies on human operators, leading to inefficiencies. Industrial Visual Anomaly Detection (IVAD) has emerged as a promising solution, with methods such as zero-shot, few-shot, and reconstruct…
The sound mixture separation is still challenging due to heavy sound overlapping and disturbance from noise. Unsupervised separation would significantly increase the difficulty. As sound overlapping always hinders accurate sound separation, we propose an Independency Adversarial Learning based Cross…
Sounding source localization is a challenging cross-modal task due to the difficulty of cross-modal alignment. Although supervised cross-modal methods achieve encouraging performance, heavy manual annotations are expensive and inefficient. Thus it is valuable and meaningful to develop unsupervised…
We address the problem of localizing a specific moment from an untrimmed video by a language sentence query. Generally, previous methods mainly exist two problems that are not fully solved: 1) How to effectively model the fine-grained visual-language alignment between video and language query? 2) Ho…
Multi-Source Domain Adaptation (MSDA), which dedicates to transfer the knowledge learned from multiple source domains to an unlabeled target domain, has drawn increasing attention in the research community. By assuming that the source and target domains share consistent key feature representations a…
Graph neural networks (GNNs) have been widely used in the 3D human pose estimation task, since the pose representation of a human body can be naturally modeled by the graph structure. Generally, most of the existing GNN-based models utilize the restricted receptive fields of filters and single-scale i…
One of the widespread solutions for non-rigid tracking has a nested-loop structure: with Gauss-Newton to minimize a tracking objective in the outer loop, and Preconditioned Conjugate Gradient (PCG) to solve a sparse linear system in the inner loop. In this paper, we employ learnable optimizations to…
Cross-modal matching has been a highlighted research topic in both vision and language areas. Learning appropriate mining strategy to sample and weight informative pairs is crucial for the cross-modal matching performance. However, most existing metric learning methods are developed for unimodal mat…