11 papers
Multi-label Classification with Panoptic Context Aggregation Networks
Mingyuan Jiu, Hailong Zhu, Wenchuan Wei +3
Context modeling is crucial for visual recognition, enabling highly discriminative image representations by integrating both intrinsic and extrinsic relationships between objects a…
Active Learning for GCN-based Action Recognition
Hichem Sahbi
Despite the notable success of graph convolutional networks (GCNs) in skeleton-based action recognition, their performance often depends on large volumes of labeled data, which are…
Label-Efficient Skeleton-based Recognition with Stable-Invertible Graph Convolutional Networks
Hichem Sahbi
Skeleton-based action recognition is a hotspot in image processing. A key challenge of this task lies in its dependence on large, manually labeled datasets whose acquisition is cos…
Image augmentation with invertible networks in interactive satellite image change detection
Hichem Sahbi
This paper devises a novel interactive satellite image change detection algorithm based on active learning. Our framework employs an iterative process that leverages a question-and…
Label-frugal satellite image change detection with generative virtual exemplar learning
Hichem Sahbi
Change detection is a major task in remote sensing which consists in finding all the occurrences of changes in multi-temporal satellite or aerial images. The success of existing me…
Deep Generative Continual Learning using Functional LoRA: FunLoRA
Victor Enescu, Hichem Sahbi
Continual adaptation of deep generative models holds tremendous potential and critical importance, given their rapid and expanding usage in text and vision based applications. Incr…