Zobrazeno 1 - 10
of 6 097
pro vyhledávání: '"Chan, Wing"'
In the testing-retraining pipeline for enhancing the robustness property of deep learning (DL) models, many state-of-the-art robustness-oriented fuzzing techniques are metric-oriented. The pipeline generates adversarial examples as test cases via suc
Externí odkaz:
http://arxiv.org/abs/2407.12428
Text-to-video retrieval answers user queries through search by concepts and embeddings. Limited by the size of the concept bank and the amount of training data, answering queries in the wild is not always effective due to the out-of-vocabulary proble
Externí odkaz:
http://arxiv.org/abs/2407.12341
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 effectiveness of existing approaches is bottlenecked by the small sizes of ava
Externí odkaz:
http://arxiv.org/abs/2404.06173
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 networks with impressive segmentation quality and fast computation. Nonethe
Externí odkaz:
http://arxiv.org/abs/2306.15910
Autor:
Hou, Zhijian, Ji, Lei, Gao, Difei, Zhong, Wanjun, Yan, Kun, Li, Chao, Chan, Wing-Kwong, Ngo, Chong-Wah, Duan, Nan, Shou, Mike Zheng
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 egocentric feature extractor and a powerful grounding model are required. Mot
Externí odkaz:
http://arxiv.org/abs/2306.15255
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 works carry out the learning of such space by assuming that all the imag
Externí odkaz:
http://arxiv.org/abs/2304.07387
Autor:
Hou, Zhijian, Zhong, Wanjun, Ji, Lei, Gao, Difei, Yan, Kun, Chan, Wing-Kwong, Ngo, Chong-Wah, Shou, Zheng, Duan, Nan
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-fiNE alignment framework. Specifically, CONE dynamically slices the l
Externí odkaz:
http://arxiv.org/abs/2211.08776
Autor:
Hou, Zhijian, Zhong, Wanjun, Ji, Lei, Gao, Difei, Yan, Kun, Chan, Wing-Kwong, Ngo, Chong-Wah, Shou, Zheng, Duan, Nan
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 short videos, long videos are also highly demanded but less explored, w
Externí odkaz:
http://arxiv.org/abs/2209.10918
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 latent space, however, is often treated as a black-box data-driven trai
Externí odkaz:
http://arxiv.org/abs/2207.00282
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 recipe-image pairs covering the majority of cuisines for supervised le
Externí odkaz:
http://arxiv.org/abs/2205.03891