3 code implementations • IEEE 2021 • Peng-Tao Jiang, Chang-Bin Zhang, Qibin Hou, Ming-Ming Cheng, Yunchao Wei
To evaluate the quality of the class activation maps produced by LayerCAM, we apply them to weakly-supervised object localization and semantic segmentation.
1 code implementation • 15 Nov 2021 • Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R. Martin, Ming-Ming Cheng, Shi-Min Hu
Humans can naturally and effectively find salient regions in complex scenes.
2 code implementations • 25 Nov 2020 • Chang-Bin Zhang, Peng-Tao Jiang, Qibin Hou, Yunchao Wei, Qi Han, Zhen Li, Ming-Ming Cheng
Experiments demonstrate that based on the same classification models, the proposed approach can effectively improve the classification performance on CIFAR-100, ImageNet, and fine-grained datasets.
1 code implementation • CVPR 2023 • Jiaxiong Qiu, Peng-Tao Jiang, Yifan Zhu, Ze-Xin Yin, Ming-Ming Cheng, Bo Ren
To remedy this issue, we present a novel surface reconstruction framework, NeuS-HSR, based on implicit neural rendering.
2 code implementations • ICCV 2019 • Peng-Tao Jiang, Qibin Hou, Yang Cao, Ming-Ming Cheng, Yunchao Wei, Hong-Kai Xiong
In order to accumulate the discovered different object parts, we propose an online attention accumulation (OAA) strategy which maintains a cumulative attention map for each target category in each training image so that the integral object regions can be gradually promoted as the training goes.
1 code implementation • CVPR 2022 • Peng-Tao Jiang, YuQi Yang, Qibin Hou, Yunchao Wei
Our framework conducts the global network to learn the captured rich object detail knowledge from a global view and thereby produces high-quality attention maps that can be directly used as pseudo annotations for semantic segmentation networks.
Ranked #16 on Weakly-Supervised Semantic Segmentation on PASCAL VOC 2012 test (using extra training data)
1 code implementation • 26 Mar 2024 • YuQi Yang, Peng-Tao Jiang, Qibin Hou, Hao Zhang, Jinwei Chen, Bo Li
Furthermore, to control the parameters and computational cost brought by the increase in the number of experts, we take inspiration from LoRA and propose to leverage the low-rank format of a vanilla convolution in the expert network.
1 code implementation • ICCV 2021 • Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang, Ming-Ming Cheng, Feng Mao
In this paper, we address the problem of personalized image segmentation.
1 code implementation • 6 Mar 2023 • Peng-Tao Jiang, YuQi Yang, Yang Cao, Qibin Hou, Ming-Ming Cheng, Chunhua Shen
To date, most existing datasets focus on autonomous driving scenes.
1 code implementation • 29 Nov 2023 • Yurui Zhu, Xueyang Fu, Peng-Tao Jiang, Hao Zhang, Qibin Sun, Jinwei Chen, Zheng-Jun Zha, Bo Li
This research focuses on the issue of single-image reflection removal (SIRR) in real-world conditions, examining it from two angles: the collection pipeline of real reflection pairs and the perception of real reflection locations.
no code implementations • NeurIPS 2018 • Qibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng
To test the quality of the generated attention maps, we employ the mined object regions as heuristic cues for learning semantic segmentation models.
no code implementations • 23 Jan 2022 • Ming-Ming Cheng, Peng-Tao Jiang, Ling-Hao Han, Liang Wang, Philip Torr
The proposed framework can generate a deep hierarchy of strongly associated supporting evidence for the network decision, which provides insight into the decision-making process.
no code implementations • 2 May 2023 • Peng-Tao Jiang, YuQi Yang
Weakly supervised semantic segmentation with weak labels is a long-lived ill-posed problem.
no code implementations • 6 Jun 2023 • Yanwen Fang, Jintai Chen, Peng-Tao Jiang, Chao Li, Yifeng Geng, Eddy K. F. LAM, Guodong Li
Multi-person motion prediction is a challenging task, especially for real-world scenarios of highly interacted persons.
no code implementations • 17 Oct 2023 • Lv Tang, Peng-Tao Jiang, Hao-Ke Xiao, Bo Li
The realm of computer vision has witnessed a paradigm shift with the advent of foundational models, mirroring the transformative influence of large language models in the domain of natural language processing.
no code implementations • 19 Nov 2023 • Lv Tang, Peng-Tao Jiang, Zhihao Shen, Hao Zhang, Jinwei Chen, Bo Li
Large Vision-Language Model (LVLM) has seen burgeoning development and increasing attention recently.
no code implementations • 8 Dec 2023 • Xi Wang, Xueyang Fu, Peng-Tao Jiang, Jie Huang, Mi Zhou, Bo Li, Zheng-Jun Zha
The former facilitates channel-dependent degradation removal operation, allowing the network to tailor responses to various adverse weather types; the latter, by integrating Fourier's global properties into channel-independent content features, enhances network capacity for consistent global content reconstruction.
no code implementations • 4 Mar 2024 • Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
Generative models have shown strong generation ability while efficient likelihood estimation is less explored.
no code implementations • 21 Mar 2024 • YuQi Yang, Peng-Tao Jiang, Jing Wang, Hao Zhang, Kai Zhao, Jinwei Chen, Bo Li
Multi-modal large language models (MLLMs) can understand image-language prompts and demonstrate impressive reasoning ability.