no code implementations • 19 Dec 2023 • Jinghao Zhou, Tomas Jakab, Philip Torr, Christian Rupprecht
Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs.
1 code implementation • CVPR 2023 • Jinghao Zhou, Li Dong, Zhe Gan, Lijuan Wang, Furu Wei
Contrastive language-image pre-training (CLIP) serves as a de-facto standard to align images and texts.
1 code implementation • 8 Sep 2022 • Xingbin Liu, Jinghao Zhou, Tao Kong, Xianming Lin, Rongrong Ji
Masked autoencoders have become popular training paradigms for self-supervised visual representation learning.
1 code implementation • 15 Nov 2021 • Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, Tao Kong
We present a self-supervised framework iBOT that can perform masked prediction with an online tokenizer.
Ranked #3 on Unsupervised Image Classification on ImageNet
1 code implementation • 29 Sep 2021 • Guotai Wang, Shuwei Zhai, Giovanni Lasio, Baoshe Zhang, Byong Yi, Shifeng Chen, Thomas J. Macvittie, Dimitris Metaxas, Jinghao Zhou, Shaoting Zhang
Computed Tomography (CT) plays an important role in monitoring radiation-induced Pulmonary Fibrosis (PF), where accurate segmentation of the PF lesions is highly desired for diagnosis and treatment follow-up.
no code implementations • ICLR 2022 • Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, Tao Kong
The success of language Transformers is primarily attributed to the pretext task of masked language modeling (MLM), where texts are first tokenized into semantically meaningful pieces.
no code implementations • 30 Apr 2021 • Weidong Lin, Yuyan Deng, Yang Gao, Ning Wang, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang
Given a query patch from a novel class, one-shot object detection aims to detect all instances of that class in a target image through the semantic similarity comparison.
no code implementations • 18 Mar 2021 • Jinghao Zhou, Bo Li, Peng Wang, Peixia Li, Weihao Gan, Wei Wu, Junjie Yan, Wanli Ouyang
Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL).
no code implementations • 18 Mar 2021 • Jinghao Zhou, Bo Li, Lei Qiao, Peng Wang, Weihao Gan, Wei Wu, Junjie Yan, Wanli Ouyang
Visual Object Tracking (VOT) has synchronous needs for both robustness and accuracy.
no code implementations • 9 Mar 2021 • Lu Yang, Hongbang Liu, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang, Yanning Zhang
Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under different viewpoints.
no code implementations • 9 Mar 2021 • Bingliang Jiao, Xin Tan, Jinghao Zhou, Lu Yang, Yunlong Wang, Peng Wang
The proposed model is composed of three main branches where a self-guided dynamic branch is constructed to strengthen instance-specific features, focusing on every single image.
1 code implementation • 6 Sep 2019 • Jinghao Zhou, Peng Wang, Haoyang Sun
The problem of visual object tracking has traditionally been handled by variant tracking paradigms, either learning a model of the object's appearance exclusively online or matching the object with the target in an offline-trained embedding space.