no code implementations • 23 May 2023 • Harman Singh, Pengchuan Zhang, Qifan Wang, Mengjiao Wang, Wenhan Xiong, Jingfei Du, Yu Chen
Along with this, we propose novel negative mining techniques in the scene graph space for improving attribute binding and relation understanding.
Ranked #1 on Image Retrieval on CREPE (Compositional REPresentation Evaluation) (Recall@1 (HN-Comp, UC) metric)
no code implementations • 21 Feb 2023 • Yunzhong He, Yuxin Tian, Mengjiao Wang, Feier Chen, Licheng Yu, Maolong Tang, Congcong Chen, Ning Zhang, Bin Kuang, Arul Prakash
In this paper we presents Que2Engage, a search EBR system built towards bridging the gap between retrieval and ranking for end-to-end optimizations.
no code implementations • 26 Oct 2022 • Suvir Mirchandani, Licheng Yu, Mengjiao Wang, Animesh Sinha, WenWen Jiang, Tao Xiang, Ning Zhang
Additionally, these works have mainly been restricted to multimodal understanding tasks.
no code implementations • 10 Mar 2022 • Jie Lei, Xinlei Chen, Ning Zhang, Mengjiao Wang, Mohit Bansal, Tamara L. Berg, Licheng Yu
In this work, we propose LoopITR, which combines them in the same network for joint learning.
no code implementations • CVPR 2022 • Mingyang Zhou, Licheng Yu, Amanpreet Singh, Mengjiao Wang, Zhou Yu, Ning Zhang
We adapt our pre-trained model to a set of V+L downstream tasks, including VQA, NLVR2, Visual Entailment, and RefCOCO+.
no code implementations • 30 Mar 2020 • Mengjiao Wang, Hikaru Ichijo, Bob Xiao
Anonymity is one of the most important qualities of blockchain technology.
no code implementations • 28 Nov 2017 • Mengjiao Wang, Zhixin Shu, Shiyang Cheng, Yannis Panagakis, Dimitris Samaras, Stefanos Zafeiriou
Several factors contribute to the appearance of an object in a visual scene, including pose, illumination, and deformation, among others.
no code implementations • CVPR 2017 • Mengjiao Wang, Yannis Panagakis, Patrick Snape, Stefanos Zafeiriou
To extract these modes of variations from visual data, several supervised methods, such as the TensorFaces, that rely on multilinear (tensor) decomposition (e. g., Higher Order SVD) have been developed.
no code implementations • 20 Apr 2017 • Ziqiang Shi, Liu Liu, Mengjiao Wang, Rujie Liu
However, in practical use, when using multi-task learned network as feature extractor, the extracted feature are always attached to several labels.