41 citations · 47 across the 10 of their papers we have counts for
10 papers
Multimodal LLM-based Query Paraphrasing for Video Search
Jiaxin Wu, Chong-Wah Ngo, Wing-Kwong Chan +3
Text-to-video retrieval answers user queries through searches based on concepts and embeddings. However, due to limitations in the size of the concept bank and the amount of traini…
Improving Interpretable Embeddings for Ad-hoc Video Search with Generative Captions and Multi-word Concept Bank
Jiaxin Wu, Chong-Wah Ngo, Wing-Kwong Chan
Aligning a user query and video clips in cross-modal latent space and that with semantic concepts are two mainstream approaches for ad-hoc video search (AVS). However, the effectiv…
Incremental Learning on Food Instance Segmentation
Huu-Thanh Nguyen, Yu Cao, Chong-Wah Ngo +1
Food instance segmentation is essential to estimate the serving size of dishes in a food image. The recent cutting-edge techniques for instance segmentation are deep learning netwo…
GroundNLQ @ Ego4D Natural Language Queries Challenge 2023
Zhijian Hou, Lei Ji, Difei Gao +7
In this report, we present our champion solution for Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2023. Essentially, to accurately ground in a video, an effective egocent…
Cross-domain Food Image-to-Recipe Retrieval by Weighted Adversarial Learning
Bin Zhu, Chong-Wah Ngo, Jingjing Chen +1
Food image-to-recipe aims to learn an embedded space linking the rich semantics in recipes with the visual content in food image for cross-modal retrieval. The existing research wo…
An Efficient COarse-to-fiNE Alignment Framework @ Ego4D Natural Language Queries Challenge 2022
Zhijian Hou, Wanjun Zhong, Lei Ji +6
This technical report describes the CONE approach for Ego4D Natural Language Queries (NLQ) Challenge in ECCV 2022. We leverage our model CONE, an efficient window-centric COarse-to…
CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding
Zhijian Hou, Wanjun Zhong, Lei Ji +6
This paper tackles an emerging and challenging problem of long video temporal grounding~(VTG) that localizes video moments related to a natural language (NL) query. Compared with s…
(Un)likelihood Training for Interpretable Embedding
Jiaxin Wu, Chong-Wah Ngo, Wing-Kwong Chan +1
Cross-modal representation learning has become a new normal for bridging the semantic gap between text and visual data. Learning modality agnostic representations in a continuous l…
Cross-lingual Adaptation for Recipe Retrieval with Mixup
Bin Zhu, Chong-Wah Ngo, Jingjing Chen +1
Cross-modal recipe retrieval has attracted research attention in recent years, thanks to the availability of large-scale paired data for training. Nevertheless, obtaining adequate…
CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval
Zhijian Hou, Chong-Wah Ngo, Wing Kwong Chan
This paper tackles a recently proposed Video Corpus Moment Retrieval task. This task is essential because advanced video retrieval applications should enable users to retrieve a pr…