6 papers · 1 filter
Fire and Smoke Detection with Burning Intensity Representation
Xiaoyi Han, Yanfei Wu, Nan Pu +4
An effective Fire and Smoke Detection (FSD) and analysis system is of paramount importance due to the destructive potential of fire disasters. However, many existing FSD methods di…
Benchmarking Multi-Scene Fire and Smoke Detection
Xiaoyi Han, Nan Pu, Zunlei Feng +4
The current irregularities in existing public Fire and Smoke Detection (FSD) datasets have become a bottleneck in the advancement of FSD technology. Upon in-depth analysis, we iden…
Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery
Haiyang Zheng, Nan Pu, Wenjing Li +2
In this paper, we study a practical yet challenging task, On-the-fly Category Discovery (OCD), aiming to online discover the newly-coming stream data that belong to both known and…
Discriminative Anchor Learning for Efficient Multi-view Clustering
Yalan Qin, Nan Pu, Hanzhou Wu +1
Multi-view clustering aims to study the complementary information across views and discover the underlying structure. For solving the relatively high computational cost for the exi…
Novel Class Discovery for Ultra-Fine-Grained Visual Categorization
Yu Liu, Yaqi Cai, Qi Jia +3
Ultra-fine-grained visual categorization (Ultra-FGVC) aims at distinguishing highly similar sub-categories within fine-grained objects, such as different soybean cultivars. Compare…
Textual Knowledge Matters: Cross-Modality Co-Teaching for Generalized Visual Class Discovery
Haiyang Zheng, Nan Pu, Wenjing Li +2
In this paper, we study the problem of Generalized Category Discovery (GCD), which aims to cluster unlabeled data from both known and unknown categories using the knowledge of labe…