no code implementations • ECCV 2020 • Xiaojie Li, Jianlong Wu, Hongyu Fang, Yue Liao, Fei Wang, Chen Qian
Sufficient knowledge extraction from the teacher network plays a critical role in the knowledge distillation task to improve the performance of the student network.
1 code implementation • 18 Mar 2024 • Xiaojie Li, Yibo Yang, Xiangtai Li, Jianlong Wu, Yue Yu, Bernard Ghanem, Min Zhang
To tackle these challenges, we present GenView, a controllable framework that augments the diversity of positive views leveraging the power of pretrained generative models while preserving semantics.
no code implementations • 19 Feb 2024 • Yuxuan Yue, Zhihang Yuan, Haojie Duanmu, Sifan Zhou, Jianlong Wu, Liqiang Nie
Large Language Models (LLMs) face significant deployment challenges due to their substantial memory requirements and the computational demands of auto-regressive text generation process.
1 code implementation • 31 Jan 2024 • Xingning Dong, Qingpei Guo, Tian Gan, Qing Wang, Jianlong Wu, Xiangyuan Ren, Yuan Cheng, Wei Chu
By employing one shared BERT-type network to refine textual and cross-modal features simultaneously, SNP is lightweight and could support various downstream applications.
1 code implementation • 25 Sep 2023 • Rui Shao, Tianxing Wu, Jianlong Wu, Liqiang Nie, Ziwei Liu
HAMMER performs 1) manipulation-aware contrastive learning between two uni-modal encoders as shallow manipulation reasoning, and 2) modality-aware cross-attention by multi-modal aggregator as deep manipulation reasoning.
1 code implementation • 14 Aug 2023 • Tian Gan, Xiao Wang, Yan Sun, Jianlong Wu, Qingpei Guo, Liqiang Nie
The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query.
2 code implementations • 3 Aug 2023 • Yibo Yang, Haobo Yuan, Xiangtai Li, Jianlong Wu, Lefei Zhang, Zhouchen Lin, Philip Torr, DaCheng Tao, Bernard Ghanem
Beyond the normal case, long-tail class incremental learning and few-shot class incremental learning are also proposed to consider the data imbalance and data scarcity, respectively, which are common in real-world implementations and further exacerbate the well-known problem of catastrophic forgetting.
1 code implementation • 15 Mar 2023 • Xiao Wang, Tian Gan, Yinwei Wei, Jianlong Wu, Dai Meng, Liqiang Nie
Existing methods mostly focus on analyzing video content, neglecting users' social influence and tag relation.
1 code implementation • CVPR 2023 • Jianlong Wu, Haozhe Yang, Tian Gan, Ning Ding, Feijun Jiang, Liqiang Nie
In the meantime, we make full use of the structured information in the hierarchical labels to learn an accurate affinity graph for contrastive learning.
no code implementations • 24 Jul 2022 • Yudong Han, Liqiang Nie, Jianhua Yin, Jianlong Wu, Yan Yan
Several studies have recently pointed that existing Visual Question Answering (VQA) models heavily suffer from the language prior problem, which refers to capturing superficial statistical correlations between the question type and the answer whereas ignoring the image contents.
no code implementations • 21 Jul 2022 • Yudong Han, Jianhua Yin, Jianlong Wu, Yinwei Wei, Liqiang Nie
Visual Question Answering (VQA) is fundamentally compositional in nature, and many questions are simply answered by decomposing them into modular sub-problems.
1 code implementation • 12 Jul 2022 • Luting Wang, Xiaojie Li, Yue Liao, Zeren Jiang, Jianlong Wu, Fei Wang, Chen Qian, Si Liu
We observe that the core difficulty for heterogeneous KD (hetero-KD) is the significant semantic gap between the backbone features of heterogeneous detectors due to the different optimization manners.
1 code implementation • CVPR 2022 • Xingning Dong, Tian Gan, Xuemeng Song, Jianlong Wu, Yuan Cheng, Liqiang Nie
Scene Graph Generation, which generally follows a regular encoder-decoder pipeline, aims to first encode the visual contents within the given image and then parse them into a compact summary graph.
Ranked #1 on Unbiased Scene Graph Generation on Visual Genome (mR@20 metric)
1 code implementation • CVPR 2022 • Tiancheng Shen, Yuechen Zhang, Lu Qi, Jason Kuen, Xingyu Xie, Jianlong Wu, Zhe Lin, Jiaya Jia
To segment 4K or 6K ultra high-resolution images needs extra computation consideration in image segmentation.
1 code implementation • ACM Special Interest Group on Information Retrieval 2021 • Leigang Qu, Meng Liu, Jianlong Wu, Zan Gao, Liqiang Nie
To address these issues, we develop a novel modality interaction modeling network based upon the routing mechanism, which is the first unified and dynamic multimodal interaction framework towards image-text retrieval.
1 code implementation • ICCV 2021 • Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua
On the other hand, a novel graph-based contrastive learning strategy is proposed to learn more compact clustering assignments.
no code implementations • 1 Jan 2021 • Xingyu Xie, Hao Kong, Jianlong Wu, Guangcan Liu, Zhouchen Lin
First of all, to perform matrix inverse, we provide a differentiable yet efficient way, named LD-Minv, which is a learnable deep neural network (DNN) with each layer being an $L$-th order matrix polynomial.
1 code implementation • NeurIPS 2020 • Shangchen Du, Shan You, Xiaojie Li, Jianlong Wu, Fei Wang, Chen Qian, ChangShui Zhang
In this paper, we examine the diversity of teacher models in the gradient space and regard the ensemble knowledge distillation as a multi-objective optimization problem so that we can determine a better optimization direction for the training of student network.
no code implementations • 20 Aug 2020 • Liangming Pan, Jingjing Chen, Jianlong Wu, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Yu-Gang Jiang, Tat-Seng Chua
Understanding food recipe requires anticipating the implicit causal effects of cooking actions, such that the recipe can be converted into a graph describing the temporal workflow of the recipe.
1 code implementation • ICML 2020 • Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin
While successful in many fields, deep neural networks (DNNs) still suffer from some open problems such as bad local minima and unsatisfactory generalization performance.
no code implementations • 23 Nov 2019 • Yibo Yang, Jianlong Wu, Hongyang Li, Xia Li, Tiancheng Shen, Zhouchen Lin
We establish a stability condition for ResNets with step sizes and weight parameters, and point out the effects of step sizes on the stability and performance.
1 code implementation • 18 Nov 2019 • Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, Zhouchen Lin
In order to overcome the lack of supervision, we introduce a differentiable module to resolve the overlap between any pair of instances.
Ranked #8 on Panoptic Segmentation on Cityscapes test
5 code implementations • ICCV 2019 • Xia Li, Zhisheng Zhong, Jianlong Wu, Yibo Yang, Zhouchen Lin, Hong Liu
It is designed to compute the representation of each position by a weighted sum of the features at all positions.
Ranked #11 on Semantic Segmentation on COCO-Stuff test
1 code implementation • 15 May 2019 • Xingyu Xie, Jianlong Wu, Zhisheng Zhong, Guangcan Liu, Zhouchen Lin
Recently, a number of learning-based optimization methods that combine data-driven architectures with the classical optimization algorithms have been proposed and explored, showing superior empirical performance in solving various ill-posed inverse problems, but there is still a scarcity of rigorous analysis about the convergence behaviors of learning-based optimization.
1 code implementation • ICCV 2019 • Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, Hongbin Zha
Recent developed deep unsupervised methods allow us to jointly learn representation and cluster unlabelled data.
Ranked #7 on Image Clustering on Tiny-ImageNet
1 code implementation • 9 Nov 2018 • Xingyu Xie, Jianlong Wu, Guangcan Liu, Jun Wang
To tackle this issue, we propose a novel method for matrix recovery in this paper, which could well handle the case where the target matrix is low-rank in an implicit feature space but high-rank or even full-rank in its original form.
no code implementations • ECCV 2018 • Xia Li, Jianlong Wu, Zhouchen Lin, Hong Liu, Hongbin Zha
In heavy rain, rain streaks have various directions and shapes, which can be regarded as the accumulation of multiple rain streak layers.
Ranked #7 on Single Image Deraining on Test2800
no code implementations • 10 Jul 2018 • Jianlong Wu, Zhouchen Lin, Hongbin Zha
In this paper, we focus on the Markov chain based spectral clustering method and propose a novel essential tensor learning method to explore the high order correlations for multi-view representation.