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Mengyuan Chen

7 accepted papers

2024

Conjugated Semantic Pool Improves OOD Detection with Pre-trained Vision-Language Models

NeurIPS 2024poster

A straightforward pipeline for zero-shot out-of-distribution (OOD) detection involves selecting potential OOD labels from an extensive semantic pool and then leveraging a pre-trained vision-language model to perform classification on both in-distribution (ID) and OOD labels. In this paper, we theori…

2023

Cascade Evidential Learning for Open-World Weakly-Supervised Temporal Action Localization

CVPR 2023poster

Targeting at recognizing and localizing action instances with only video-level labels during training, Weakly-supervised Temporal Action Localization (WTAL) has achieved significant progress in recent years. However, living in the dynamically changing open world where unknown actions constantly spri…

Cited by 21SourcePDFScholar
2023

Collecting Cross-Modal Presence-Absence Evidence for Weakly-Supervised Audio-Visual Event Perception

CVPR 2023poster

With only video-level event labels, this paper targets at the task of weakly-supervised audio-visual event perception (WS-AVEP), which aims to temporally localize and categorize events belonging to each modality. Despite the recent progress, most existing approaches either ignore the unsynchronized…

2022

Dual-Evidential Learning for Weakly-Supervised Temporal Action Localization

ECCV 2022poster

"Weakly-supervised temporal action localization (WS-TAL) aims to localize the action instances and recognize their categories with only video-level labels. Despite great progress, existing methods suffer from severe action-background ambiguity, which mainly comes from background noise introduced by…

2022

Fine-Grained Temporal Contrastive Learning for Weakly-Supervised Temporal Action Localization

CVPR 2022poster

We target at the task of weakly-supervised action localization (WSAL), where only video-level action labels are available during model training. Despite the recent progress, existing methods mainly embrace a localization-by-classification paradigm and overlook the fruitful fine-grained temporal dist…

Cited by 104PDFcodeScholar
2021

Fast Hierarchy Preserving Graph Embedding via Subspace Constraints

ICASSP 2021accepted

Hierarchy preserving network embedding is a method that project nodes into feature space by preserving the hierarchy property of networks. Recently, researches on network representation have considerably profited from taking hierarchy into consideration. Among these works, SpaceNE <sup xmlns:mml="ht…

Cited by 0SourceScholar