no code implementations • 5 Apr 2024 • Xize Liang, Chao Chen, Jie Wang, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye
The preference alignment aims to enable large language models (LLMs) to generate responses that conform to human values, which is essential for developing general AI systems.
1 code implementation • 2 Apr 2024 • Yansong Peng, Hebei Li, Yueyi Zhang, Xiaoyan Sun, Feng Wu
However, they display inadequate sparsity and adaptability when applied to event-based object detection, since these approaches cannot balance the fine granularity of token-level sparsification and the efficiency of window-based Transformers, leading to reduced performance and efficiency.
no code implementations • 18 Mar 2024 • Zhuoyuan Li, Zikun Yuan, Li Li, Dong Liu, Xiaohu Tang, Feng Wu
Moreover, segmentation mask is considered in the joint rate-distortion optimization for motion estimation and partition estimation to derive the motion vector of different regions and partition more accurately.
no code implementations • 17 Jan 2024 • Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
To the best of our knowledge, SKR is the first attempt to address the time-consuming nature of data generation for learning neural operators.
2 code implementations • 12 Jan 2024 • Xiaoyu Liu, Yueyi Zhang, Zhiwei Xiong, Wei Huang, Bo Hu, Xiaoyan Sun, Feng Wu
IGD constructs a graph representing instance features and relations, transferring these two types of knowledge by enforcing instance graph consistency.
1 code implementation • 5 Jan 2024 • Qihua Chen, Xuejin Chen, Chenxuan Wang, Yixiong Liu, Zhiwei Xiong, Feng Wu
In this work, we aim to reduce human workload by predicting connectivity between over-segmented neuron pieces, taking both microscopy image and 3D morphology features into account, similar to human proofreading workflow.
no code implementations • 1 Jan 2024 • Shi Yin, Xinyang Pan, XUDONG ZHU, Tianyu Gao, Haochong Zhang, Feng Wu, Lixin He
Deep learning for predicting the electronic structure Hamiltonian of quantum systems necessitates satisfying the covariance laws, among which achieving SO(3)-equivariance without sacrificing the non-linear expressive capability of networks remains unsolved.
1 code implementation • 3 Dec 2023 • Langtian Qin, Hancheng Lu, Yuang Chen, Baolin Chong, Feng Wu
In the traditional cellular-based mobile edge computing (MEC), users at the edge of the cell are prone to suffer severe inter-cell interference and signal attenuation, leading to low throughput even transmission interruptions.
no code implementations • 22 Oct 2023 • Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu
To tackle this problem, we propose a novel approach, which is called Adversarial Instance Augmentation and does not require to know the problem type for new instance generation, to promote data diversity for learning-based branching modules in the branch-and-bound (B&B) Solvers (AdaSolver).
no code implementations • 18 Oct 2023 • Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu
Specifically, we formulate the routine design task as a Markov decision process and propose an RL framework with adaptive action sequences to generate high-quality presolve routines efficiently.
1 code implementation • NeurIPS 2023 • Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu
In the past few years, there has been an explosive surge in the use of machine learning (ML) techniques to address combinatorial optimization (CO) problems, especially mixed-integer linear programs (MILPs).
1 code implementation • ICCV 2023 • Yansong Peng, Yueyi Zhang, Zhiwei Xiong, Xiaoyan Sun, Feng Wu
Event cameras are a type of novel neuromorphic sen-sor that has been gaining increasing attention.
1 code implementation • 26 Sep 2023 • Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu
The inverse mapping leads to an objective function that is equivalent to that by the joint training, while it can effectively incorporate GNNs in the training phase of NEs against the learning bias.
Ranked #1 on Node Property Prediction on ogbn-proteins
2 code implementations • 22 Sep 2023 • Wei Zhai, Pingyu Wu, Kai Zhu, Yang Cao, Feng Wu, Zheng-Jun Zha
In addition, our method also achieves state-of-the-art weakly supervised semantic segmentation performance on the PASCAL VOC 2012 and MS COCO 2014 datasets.
no code implementations • 20 Sep 2023 • Jie Wang, Hanzhu Chen, Qitan Lv, Zhihao Shi, Jiajun Chen, Huarui He, Hongtao Xie, Yongdong Zhang, Feng Wu
This implies the great potential of the semantic correlations for the entity-independent inductive link prediction task.
1 code implementation • 22 Aug 2023 • Zhihai Wang, Lei Chen, Jie Wang, Xing Li, Yinqi Bai, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu
In particular, we notice that the runtime of the Resub and Mfs2 operators often dominates the overall runtime of LS optimization processes.
1 code implementation • 20 Apr 2023 • Shaokai Liu, Hao Feng, Wengang Zhou, Houqiang Li, Cong Liu, Feng Wu
Tremendous efforts have been made on document image rectification, but how to learn effective representation of such distorted images is still under-explored.
no code implementations • CVPR 2023 • Jiahuan Yu, Jiahao Chang, Jianfeng He, Tianzhu Zhang, Feng Wu
To deal with the above issues, we propose Adaptive Spot-Guided Transformer (ASTR) for local feature matching, which jointly models the local consistency and scale variations in a unified coarse-to-fine architecture.
no code implementations • 17 Mar 2023 • Jie Wang, Zhihao Shi, Xize Liang, Shuiwang Ji, Bin Li, Feng Wu
During the message passing (MP) in GNNs, subgraph-wise sampling methods discard messages outside the mini-batches in backward passes to avoid the well-known neighbor explosion problem, i. e., the exponentially increasing dependencies of nodes with the number of MP iterations.
no code implementations • 6 Mar 2023 • Feng Wu, Yuelin Zhao, Jianhua Pang, Jun Yan, Wanxie Zhong
The acceleration technique can generate a low-discrepancy sample set with a smaller dispersion, compared with a random sampling, in the expanded dimensional space; it also reduces the error at each iteration, and hence improves the convergence speed.
1 code implementation • 21 Feb 2023 • Langtian Qin, Hancheng Lu, Yuang Chen, Zhuojia Gu, Dan Zhao, Feng Wu
To achieve efficient and reliable resource utilization with user-centric services, we propose an energy efficient blockchain-enabled UC-MEC system where blockchain operations and resource optimization are jointly performed.
1 code implementation • 21 Feb 2023 • Langtian Qin, Hancheng Lu, Yao Lu, Chenwu Zhang, Feng Wu
To address single-base station (BS) transmission limitation and serious edge effect in traditional cellular-based edge service caching networks, in this paper, we proposed a novel user-centric edge service caching framework where each user is jointly provided with edge caching and wireless transmission services by a specific BS cluster instead of a single BS.
1 code implementation • 19 Feb 2023 • Jie Wang, Rui Yang, Zijie Geng, Zhihao Shi, Mingxuan Ye, Qi Zhou, Shuiwang Ji, Bin Li, Yongdong Zhang, Feng Wu
The appealing features of RSD-OA include that: (1) RSD-OA is invariant to visual distractions, as it is conditioned on the predefined subsequent action sequence without task-irrelevant information from transition dynamics, and (2) the reward sequence captures long-term task-relevant information in both rewards and transition dynamics.
no code implementations • 18 Feb 2023 • Jinming Ma, Feng Wu, Yingfeng Chen, Xianpeng Ji, Yu Ding
Specifically, we observe that these issues make conventional RL methods difficult to learn a useful state representation in the end-to-end training with multimodal information.
1 code implementation • 2 Feb 2023 • Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu
The obtained motif vocabulary consists of not only molecular motifs (i. e., the frequent fragments), but also their connection information, indicating how the motifs are connected with each other.
no code implementations • 1 Feb 2023 • Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu
Cut selection -- which aims to select a proper subset of the candidate cuts to improve the efficiency of solving MILPs -- heavily depends on (P1) which cuts should be preferred, and (P2) how many cuts should be selected.
no code implementations • CVPR 2023 • Naisong Luo, Yuwen Pan, Rui Sun, Tianzhu Zhang, Zhiwei Xiong, Feng Wu
To address these challenges, we propose a novel De-camouflaging Network (DCNet) including a pixel-level camouflage decoupling module and an instance-level camouflage suppression module.
no code implementations • CVPR 2023 • Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu
Second, the HKDL module can generate keypoint detectors in a hierarchical way, which is helpful for detecting keypoints with diverse levels of structures.
1 code implementation • ICCV 2023 • Xiaoyu Liu, Wei Huang, Zhiwei Xiong, Shenglong Zhou, Yueyi Zhang, Xuejin Chen, Zheng-Jun Zha, Feng Wu
Sparse instance-level supervision has recently been explored to address insufficient annotation in biomedical instance segmentation, which is easier to annotate crowded instances and better preserves instance completeness for 3D volumetric datasets compared to common semi-supervision. In this paper, we propose a sparsely supervised biomedical instance segmentation framework via cross-representation affinity consistency regularization.
no code implementations • CVPR 2023 • Huayu Mai, Rui Sun, Tianzhu Zhang, Zhiwei Xiong, Feng Wu
Automatic mitochondria segmentation enjoys great popularity with the development of deep learning.
no code implementations • ICCV 2023 • Rui Sun, YuAn Wang, Huayu Mai, Tianzhu Zhang, Feng Wu
In this work, we reconcile the inherent tension of spatial and temporal information to retrieve memory frame information along the object trajectory, and propose a novel and coherent Trajectory Memory Retrieval Network (TMRN) to equip with the trajectory information, including a spatial alignment module and a temporal aggregation module.
1 code implementation • 23 Dec 2022 • Zibo Wang, Pinghe Li, Chieh-Jan Mike Liang, Feng Wu, Francis Y. Yan
We present Autothrottle, a bi-level resource management framework for microservices with latency SLOs (service-level objectives).
no code implementations • 7 Oct 2022 • Ziyan Zhang, Junhao Shen, Dongwei Yao, Feng Wu
In order to increase the prediction accuracy of the online vehicle velocity prediction (VVP) strategy, a self-adaptive velocity prediction algorithm fused with traffic information was presented for the multiple scenarios.
no code implementations • 20 Sep 2022 • Yuelin Zhao, Feng Wu, Jianhua Pang, Wanxie Zhong
Heterogeneous comprehensive learning particle swarm optimization (HCLPSO) is a type of evolutionary algorithm with enhanced exploration and exploitation capabilities.
1 code implementation • 15 Sep 2022 • Gang Yang, Li Zhang, Man Zhou, Aiping Liu, Xun Chen, Zhiwei Xiong, Feng Wu
Interpretable neural network models are of significant interest since they enhance the trustworthiness required in clinical practice when dealing with medical images.
1 code implementation • 10 Aug 2022 • Huarui He, Jie Wang, Yunfei Liu, Feng Wu
The goal of single-step retrosynthesis is to identify the possible reactants that lead to the synthesis of the target product in one reaction.
no code implementations • 29 Jul 2022 • Xu Han, Feng Wu
Most reinforcement learning (RL) methods only focus on learning a single task from scratch and are not able to use prior knowledge to learn other tasks more effectively.
no code implementations • 29 Jul 2022 • Yixiang Wang, Yujing Hu, Feng Wu, Yingfeng Chen
In this paper, we propose to automatically generate goal-consistent intrinsic rewards for the agent to learn, by maximizing which the expected accumulative extrinsic rewards can be maximized.
no code implementations • 12 Jul 2022 • Shuai Huo, Dong Liu, Li Li, Siwei Ma, Feng Wu, Wen Gao
Our idea is to provide multiple discrete starting points in the global space and optimize the local optimum around each point by numerical algorithm efficiently.
no code implementations • 16 Jun 2022 • Xueliang Wang, Jianyu Cai, Shuiwang Ji, Houqiang Li, Feng Wu, Jie Wang
A major novelty of SALA is the task-adaptive metric, which can learn the metric adaptively for different tasks in an end-to-end fashion.
no code implementations • 16 Jun 2022 • Xueliang Wang, Jiajun Chen, Feng Wu, Jie Wang
By enforcing the entities' embeddings close to their associated prototypes' embeddings, our approach can effectively encourage the global semantic similarities of entities -- that can be far away in the KG -- connected by the same relation.
no code implementations • 27 May 2022 • Jinming Ma, Feng Wu
To do this, we propose two approaches: one is directly to use graph neural network (GNN) to generate the network partition, and the other is to use Monte-Carlo tree search (MCTS) to find the best partition with criteria computed by GNN.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 24 May 2022 • Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
To tackle these problems, we propose a novel Adversarial Knowledge Distillation framework for graph models named GraphAKD, which adversarially trains a discriminator and a generator to adaptively detect and decrease the discrepancy.
1 code implementation • 20 May 2022 • Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu
Generalization across different environments with the same tasks is critical for successful applications of visual reinforcement learning (RL) in real scenarios.
no code implementations • 22 Apr 2022 • Hongbin Zhang, Yu Yang, Feng Wu, Qixin Zhang
Optimizing the assortment of products to display to customers is a key to increasing revenue for both offline and online retailers.
no code implementations • 24 Mar 2022 • Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu
Semantic matching models -- which assume that entities with similar semantics have similar embeddings -- have shown great power in knowledge graph embeddings (KGE).
no code implementations • 22 Mar 2022 • Jinze Chen, Yang Wang, Yang Cao, Feng Wu, Zheng-Jun Zha
Dynamic Vision Sensor (DVS) can asynchronously output the events reflecting apparent motion of objects with microsecond resolution, and shows great application potential in monitoring and other fields.
no code implementations • 19 Mar 2022 • Qing Cai, Yiming Qian, Jinxing Li, Jun Lv, Yee-Hong Yang, Feng Wu, David Zhang
Transformer-based architectures start to emerge in single image super resolution (SISR) and have achieved promising performance.
2 code implementations • 8 Feb 2022 • Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu
Surprisingly, we observe from experiments that the graph structure modeling in GCNs does not have a significant impact on the performance of KGC models, which is in contrast to the common belief.
no code implementations • 3 Feb 2022 • Guangkai Xu, Wei Yin, Hao Chen, Chunhua Shen, Kai Cheng, Feng Wu, Feng Zhao
However, in some video-based scenarios such as video depth estimation and 3D scene reconstruction from a video, the unknown scale and shift residing in per-frame prediction may cause the depth inconsistency.
no code implementations • CVPR 2022 • Jiamin Wu, Tianzhu Zhang, Zhe Zhang, Feng Wu, Yongdong Zhang
To address this issue, we propose an end-to-end Motion-modulated Temporal Fragment Alignment Network (MTFAN) by jointly exploring the task-specific motion modulation and the multi-level temporal fragment alignment for Few-Shot Action Recognition (FSAR).
no code implementations • CVPR 2022 • Ganchao Tan, Yang Wang, Han Han, Yang Cao, Feng Wu, Zheng-Jun Zha
To recognize words from the event data, we propose a novel Multi-grained Spatio-Temporal Features Perceived Network (MSTP) to perceive fine-grained spatio-temporal features from microsecond time-resolved event data.
no code implementations • 23 Dec 2021 • Xiaotong Ni, Hui-Hai Zhao, Lei Wang, Feng Wu, Jianxin Chen
In a quantum processor, the device design and external controls together contribute to the quality of the target quantum operations.
1 code implementation • 9 Nov 2021 • Jintong Ren, Jin-Kao Hao, Feng Wu, Zhang-Hua Fu
As an extension of the traveling repairman problem with profits, the multiple traveling repairman problem with profits consists of multiple repairmen who visit a subset of all customers to maximize the revenues collected through the visited customers.
1 code implementation • NeurIPS 2021 • Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu
To address this challenge, we propose a novel query embedding model, namely Cone Embeddings (ConE), which is the first geometry-based QE model that can handle all the FOL operations, including conjunction, disjunction, and negation.
no code implementations • 30 Sep 2021 • Haichuan Ma, Dong Liu, Cunhui Dong, Li Li, Feng Wu
However, this nature was seldom considered in previous studies on image compression, which usually chose one possible image as reconstruction, e. g. the one with the maximal a posteriori probability.
2 code implementations • 11 Aug 2021 • Xiao Wang, Jianing Li, Lin Zhu, Zhipeng Zhang, Zhe Chen, Xin Li, YaoWei Wang, Yonghong Tian, Feng Wu
Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency.
Ranked #1 on Object Tracking on VisEvent
2 code implementations • 22 Jul 2021 • Xiao Wang, Xiujun Shu, Shiliang Zhang, Bo Jiang, YaoWei Wang, Yonghong Tian, Feng Wu
The visible and thermal filters will be used to conduct a dynamic convolutional operation on their corresponding input feature maps respectively.
Ranked #17 on Rgb-T Tracking on RGBT234
2 code implementations • 7 Jul 2021 • Zehui Chen, Chenhongyi Yang, Qiaofei Li, Feng Zhao, Zheng-Jun Zha, Feng Wu
Extensive experiments on MS COCO benchmark show that our approach can lead to 2. 0 mAP, 2. 4 mAP and 2. 2 mAP absolute improvements on RetinaNet, FCOS, and ATSS baselines with negligible extra overhead.
no code implementations • CVPR 2021 • Wenfei Yang, Tianzhu Zhang, Xiaoyuan Yu, Tian Qi, Yongdong Zhang, Feng Wu
To alleviate this problem, we propose a novel Uncertainty Guided Collaborative Training (UGCT) strategy, which mainly includes two key designs: (1) The first design is an online pseudo label generation module, in which the RGB and FLOW streams work collaboratively to learn from each other.
no code implementations • CVPR 2021 • Rui Sun, Yihao Li, Tianzhu Zhang, Zhendong Mao, Feng Wu, Yongdong Zhang
First, to the best of our knowledge, this is the first work to formulate lesion discovery as a weakly supervised lesion localization problem via a transformer decoder.
1 code implementation • 9 Jun 2021 • Xiao Wang, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu
In this paper, we propose a novel and general target-aware attention mechanism (termed TANet) and integrate it with tracking-by-detection framework to conduct joint local and global search for robust tracking.
no code implementations • CVPR 2021 • Yulin Li, Jianfeng He, Tianzhu Zhang, Xiang Liu, Yongdong Zhang, Feng Wu
To address these issues, we propose a novel end-to-end Part-Aware Transformer (PAT) for occluded person Re-ID through diverse part discovery via a transformer encoderdecoder architecture, including a pixel context based transformer encoder and a part prototype based transformer decoder.
no code implementations • 8 Jun 2021 • Hanting Li, Mingzhe Sui, Feng Zhao, ZhengJun Zha, Feng Wu
Facial Expression Recognition (FER) in the wild is an extremely challenging task in computer vision due to variant backgrounds, low-quality facial images, and the subjectiveness of annotators.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • CVPR 2021 • Wang Luo, Tianzhu Zhang, Wenfei Yang, Jingen Liu, Tao Mei, Feng Wu, Yongdong Zhang
In this paper, we present an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.
Ranked #7 on Weakly Supervised Action Localization on THUMOS14
Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1
2 code implementations • CVPR 2021 • Xiao Wang, Xiujun Shu, Zhipeng Zhang, Bo Jiang, YaoWei Wang, Yonghong Tian, Feng Wu
We believe this benchmark will greatly boost related researches on natural language guided tracking.
Ranked #3 on Visual Object Tracking on TNL2K (precision metric)
1 code implementation • 30 Mar 2021 • Xiao Wang, Zhe Chen, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu
In this paper, we propose to introduce more dynamics by devising a dynamic attention-guided multi-trajectory tracking strategy.
1 code implementation • 5 Mar 2021 • Jiajun Chen, Huarui He, Feng Wu, Jie Wang
TACT is inspired by the observation that the semantic correlation between two relations is highly correlated to their topological structure in knowledge graphs.
no code implementations • ICCV 2021 • Meng Meng, Tianzhu Zhang, Qi Tian, Yongdong Zhang, Feng Wu
To the best of our knowledge, this is the first work that can achieve remarkable performance for both tasks by optimizing them jointly via FAM for WSOL.
no code implementations • ICCV 2021 • Jiamin Wu, Tianzhu Zhang, Yongdong Zhang, Feng Wu
The task-aware part filters can adapt to any individual task and automatically mine task-related local parts even for an unseen task.
no code implementations • NeurIPS 2020 • Yujing Hu, Weixun Wang, Hangtian Jia, Yixiang Wang, Yingfeng Chen, Jianye Hao, Feng Wu, Changjie Fan
In this paper, we consider the problem of adaptively utilizing a given shaping reward function.
7 code implementations • ACL 2020 • Hao Tian, Can Gao, Xinyan Xiao, Hao liu, Bolei He, Hua Wu, Haifeng Wang, Feng Wu
In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair.
Ranked #14 on Stock Market Prediction on Astock
1 code implementation • CVPR 2020 • Jianping Lin, Dong Liu, Houqiang Li, Feng Wu
To compensate for the compression error of the auto-encoders, we further design a MV refinement network and a residual refinement network, taking use of the multiple reference frames as well.
1 code implementation • CVPR 2020 • Chang Chen, Zhiwei Xiong, Xiaoming Liu, Feng Wu
To reconcile these two demands, we propose Siamese Trace Erasing (SiamTE), in which a novel hybrid loss is designed on the basis of Siamese architecture for network training.
no code implementations • 28 Nov 2019 • Yixiang Wang, Feng Wu
To tackle this, we propose to train multiple policies for each agent and postpone the selection of the best policy at execution time.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 26 Nov 2019 • Yang Wang, Yang Cao, Zheng-Jun Zha, Jing Zhang, Zhiwei Xiong, Wei zhang, Feng Wu
Contrast enhancement and noise removal are coupled problems for low-light image enhancement.
no code implementations • 20 Oct 2019 • Yuhang Li, Xuejin Chen, Feng Wu, Zheng-Jun Zha
The large-scale discriminator enforces the completeness of global structures and the small-scale discriminator encourages fine details, thereby enhancing the realism of generated face images.
no code implementations • 25 Sep 2019 • Tianxiao Gao, Ruiqin Xiong, Zhenhua Liu, Siwei Ma, Feng Wu, Tiejun Huang, Wen Gao
One way to compress these heavy models is knowledge transfer (KT), in which a light student network is trained through absorbing the knowledge from a powerful teacher network.
no code implementations • 5 Aug 2019 • Ariel Soto-Caro, Feng Wu, Zhengfei Guan, Natalia Peres
The objective of our study is to propose a methodology to address the issue of an insufficient number of observations using simulations and take into account the effect of disease pressure on yield through a quantile regression model.
1 code implementation • 6 Jun 2019 • Zheng-Jun Zha, Daqing Liu, Hanwang Zhang, Yongdong Zhang, Feng Wu
With the maturity of visual detection techniques, we are more ambitious in describing visual content with open-vocabulary, fine-grained and free-form language, i. e., the task of image captioning.
1 code implementation • 29 Apr 2019 • Dong Liu, Yue Li, Jianping Lin, Houqiang Li, Feng Wu
For deep schemes, pixel probability modeling and auto-encoder are the two approaches, that can be viewed as predictive coding scheme and transform coding scheme, respectively.
Multimedia Image and Video Processing
1 code implementation • CVPR 2019 • Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha, Feng Wu
Existing methods for single image super-resolution (SR) are typically evaluated with synthetic degradation models such as bicubic or Gaussian downsampling.
no code implementations • 21 Feb 2019 • Yujiao Lu, Hancheng Lu, Liangliang Cao, Feng Wu, Daren Zhu
DRL-DPT overcomes the main obstacles in applying reinforcement learning and deep learning in wireless networks, i. e. continuous state space, continuous action space and convergence.
1 code implementation • 19 Dec 2018 • Zhibo Chen, Jianxin Lin, Tiankuang Zhou, Feng Wu
The SGU sequentially takes information from two different levels as inputs and decides the output based on one active input.
no code implementations • ICCV 2019 • Daqing Liu, Hanwang Zhang, Feng Wu, Zheng-Jun Zha
In particular, we develop a novel modular network called Neural Module Tree network (NMTree) that regularizes the visual grounding along the dependency parsing tree of the sentence, where each node is a neural module that calculates visual attention according to its linguistic feature, and the grounding score is accumulated in a bottom-up direction where as needed.
no code implementations • 21 Nov 2018 • Xueyang Fu, Qi Qi, Yue Huang, Xinghao Ding, Feng Wu, John Paisley
We propose a simple yet effective deep tree-structured fusion model based on feature aggregation for the deraining problem.
no code implementations • ECCV 2018 • Chang Chen, Zhiwei Xiong, Xinmei Tian, Feng Wu
Boosting is a classic algorithm which has been successfully applied to diverse computer vision tasks.
1 code implementation • 16 Aug 2018 • Daqing Liu, Zheng-Jun Zha, Hanwang Zhang, Yongdong Zhang, Feng Wu
To fill the gap, we propose a Context-Aware Visual Policy network (CAVP) for sequence-level image captioning.
no code implementations • 31 Jul 2018 • Shaobo Min, Xuejin Chen, Zheng-Jun Zha, Feng Wu, Yongdong Zhang
\begin{abstract} Learning-based methods suffer from a deficiency of clean annotations, especially in biomedical segmentation.
1 code implementation • 26 Jul 2018 • Fei Liang, Cong Shen, Wei Yu, Feng Wu
A deep neural network (DNN) based power control method is proposed, which aims at solving the non-convex optimization problem of maximizing the sum rate of a multi-user interference channel.
no code implementations • CVPR 2018 • Yicheng Wang, Zhenzhong Chen, Feng Wu, Gang Wang
In this paper, a novel deep architecture named BraidNet is proposed for person re-identification.
no code implementations • 26 Apr 2018 • Zhibo Chen, Tianyu He, Xin Jin, Feng Wu
One key challenge to learning-based video compression is that motion predictive coding, a very effective tool for video compression, can hardly be trained into a neural network.
Multimedia Image and Video Processing
no code implementations • 18 Sep 2017 • Rui Song, Dong Liu, Houqiang Li, Feng Wu
In this paper, we propose an arithmetic coding strategy by training neural networks, and make preliminary studies on coding of the intra prediction modes in HEVC.
Multimedia
no code implementations • 18 Jul 2017 • Fei Liang, Cong Shen, Feng Wu
The standard BP decoder is used to estimate the coded bits, followed by a CNN to remove the estimation errors of the BP decoder and obtain a more accurate estimation of the channel noise.
no code implementations • CVPR 2017 • Zhiwei Xiong, Lizhi Wang, Huiqun Li, Dong Liu, Feng Wu
This paper presents the first snapshot hyperspectral light field imager in practice.
no code implementations • 10 Mar 2017 • Ning Yan, Dong Liu, Houqiang Li, Feng Wu
To further improve the coding efficiency, sub-pel motion compensation has been utilized, which requires interpolation of fractional samples.
Multimedia
no code implementations • 22 Feb 2017 • Yue Li, Dong Liu, Houqiang Li, Li Li, Feng Wu, Hong Zhang, Haitao Yang
A block can be down-sampled before being compressed by normal intra coding, and then up-sampled to its original resolution.
Multimedia
1 code implementation • 24 Aug 2016 • Yuanying Dai, Dong Liu, Feng Wu
Lossy image and video compression algorithms yield visually annoying artifacts including blocking, blurring, and ringing, especially at low bit-rates.
Multimedia
no code implementations • 9 Jun 2016 • Dongcai Lu, Feng Wu, Xiaoping Chen
Understanding user instructions in natural language is an active research topic in AI and robotics.
no code implementations • 8 May 2016 • Saihui Hou, Zilei Wang, Feng Wu
This paper addresses the issue on how to more effectively coordinate the depth with RGB aiming at boosting the performance of RGB-D object detection.
no code implementations • 22 Nov 2015 • Haitian Zheng, Yebin Liu, Mengqi Ji, Feng Wu, Lu Fang
Finally, the optimization problem enables us to take advantage of state-of-the-art fully convolutional network structure for the implementation of the above encoders and decoder.
no code implementations • CVPR 2015 • Lizhi Wang, Zhiwei Xiong, Dahua Gao, Guangming Shi, Wen-Jun Zeng, Feng Wu
We propose a novel dual-camera design to acquire 4D high-speed hyperspectral (HSHS) videos with high spatial and spectral resolution.
no code implementations • CVPR 2014 • Lu Fang, Haifeng Liu, Feng Wu, Xiaoyan Sun, Houqiang Li
In this paper, we deal with the image deblurring problem in a completely new perspective by proposing separable kernel to represent the inherent properties of the camera and scene system.
no code implementations • CVPR 2014 • Huanjing Yue, Xiaoyan Sun, Jingyu Yang, Feng Wu
Second, to handle heavy noise, we further propose using the denoising image to improve image registration of the retrieved Web images, 3D cube building, and the estimation of filtering parameters in the frequency domain.
no code implementations • NeurIPS 2013 • Aijun Bai, Feng Wu, Xiaoping Chen
Monte-Carlo tree search is drawing great interest in the domain of planning under uncertainty, particularly when little or no domain knowledge is available.
no code implementations • 8 Sep 2013 • Feng Wu, Nicholas R. Jennings
Many multi-agent coordination problems can be represented as DCOPs.
no code implementations • CVPR 2013 • Qiang Hao, Rui Cai, Zhiwei Li, Lei Zhang, Yanwei Pang, Feng Wu, Yong Rui
3D model-based object recognition has been a noticeable research trend in recent years.
no code implementations • CVPR 2013 • Zhe Yang, Zhiwei Xiong, Yueyi Zhang, Jiao Wang, Feng Wu
First, we propose an algorithm to design the patterns to carry more phase information without compromising the depth reconstruction from a single captured image as with Kinect.