1 citations · 1 across the 5 of their papers we have counts for
8 papers
CloSeR: Unified Relational Distillation from Closed-Set Teachers for Category Discovery
Yuanpei Liu, Zhenqi He, Jialu Tang +1
Generalized Category Discovery (GCD) is an intriguing open-world problem that has garnered increasing attention: given partially labelled data, the goal is to correctly recognize k…
FlowCIR: Semantic Transport via Flow Matching for Zero-Shot Composed Image Retrieval
Zhenqi He, Ziqi Jiang, Yuanpei Liu +3
Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image by editing a reference image with a natural-language instruction, without relying on domain-specific ann…
SEAL: Semantic-Aware Hierarchical Learning for Generalized Category Discovery
Zhenqi He, Yuanpei Liu, Kai Han
This paper investigates the problem of Generalized Category Discovery (GCD). Given a partially labelled dataset, GCD aims to categorize all unlabelled images, regardless of whether…
Category Discovery: An Open-World Perspective
Zhenqi He, Yuanpei Liu, Kai Han
Category discovery (CD) is an emerging open-world learning task, which aims at automatically categorizing unlabelled data containing instances from unseen classes, given some label…
Hyperbolic Category Discovery
Yuanpei Liu, Zhenqi He, Kai Han
Generalized Category Discovery (GCD) is an intriguing open-world problem that has garnered increasing attention. Given a dataset that includes both labelled and unlabelled images,…
DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery
Yuanpei Liu, Kai Han
In this paper, we tackle the problem of Generalized Category Discovery (GCD). Given a dataset containing both labelled and unlabelled images, the objective is to categorize all ima…