no code implementations • 15 Apr 2024 • Han Xue, Qianru Sun, Li Song, Wenjun Zhang, Zhiwu Huang
Secondly, it standardizes the training of different tasks into a general in-context learning, where "in-context" means the input comprises an example input-output pair of the target task and a query image.
no code implementations • 31 Mar 2024 • Chen Peng, Zhiqin Qian, Kunyu Wang, Qi Luo, Zhuming Bi, Wenjun Zhang
In the study reported in this paper, based on the well-known hybridization principle, we proposed a method to combine CNN and Transformer to retain the strengths of both, and we applied this method to build a system called MugenNet for colonic polyp image segmentation.
1 code implementation • 26 Feb 2024 • Chunyi Li, Guo Lu, Donghui Feng, HaoNing Wu, ZiCheng Zhang, Xiaohong Liu, Guangtao Zhai, Weisi Lin, Wenjun Zhang
With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic.
no code implementations • 23 Jan 2024 • Yue Hu, Xianghe Pang, Xiaoqi Qin, Yonina C. Eldar, Siheng Chen, Ping Zhang, Wenjun Zhang
Following this strategy, we first formulate a mathematical optimization framework for the perception-communication trade-off and then propose PragComm, a multi-agent collaborative perception system with two key components: i) single-agent detection and tracking and ii) pragmatic collaboration.
1 code implementation • 9 Dec 2023 • Zijian Chen, Wei Sun, HaoNing Wu, ZiCheng Zhang, Jun Jia, Zhongpeng Ji, Fengyu Sun, Shangling Jui, Xiongkuo Min, Guangtao Zhai, Wenjun Zhang
In this paper, we take the first step to benchmark and assess the visual naturalness of AI-generated images.
no code implementations • 30 Nov 2023 • Zijian Chen, Wei Sun, ZiCheng Zhang, Ru Huang, Fangfang Lu, Xiongkuo Min, Guangtao Zhai, Wenjun Zhang
Banding artifact, as known as staircase-like contour, is a common quality annoyance that happens in compression, transmission, etc.
no code implementations • 26 Oct 2023 • Runnan Liu, Liang Liu, Yin Xu, Dazhi He, Wenjun Zhang, Chang Wen Chen
We first categorize two types of channel covariance matrix changes based on their impact on system design: Type I change, which denotes the change in the BS receive covariance matrix, and Type II change, which denotes the change in the IRS transmit/receive covariance matrix.
no code implementations • 7 Aug 2023 • Bingyan Xie, Yongpeng Wu, Yuxuan Shi, Derrick Wing Kwan Ng, Wenjun Zhang
Multi-node communication, which refers to the interaction among multiple devices, has attracted lots of attention in many Internet-of-Things (IoT) scenarios.
no code implementations • 24 Apr 2023 • Shunli Ren, Zixing Lei, Zi Wang, Mehrdad Dianati, Yafei Wang, Siheng Chen, Wenjun Zhang
To achieve comprehensive recovery, we design a communication-adaptive multi-scale spatial-temporal prediction model to extract multi-scale spatial-temporal features based on V2X communication conditions and capture the most significant information for the prediction of the missing information.
1 code implementation • CVPR 2023 • Yurong Zhang, Liulei Li, Wenguan Wang, Rong Xie, Li Song, Wenjun Zhang
Current top-leading solutions for video object segmentation (VOS) typically follow a matching-based regime: for each query frame, the segmentation mask is inferred according to its correspondence to previously processed and the first annotated frames.
1 code implementation • CVPR 2023 • Han Xue, Zhiwu Huang, Qianru Sun, Li Song, Wenjun Zhang
In this work, we explore the freestyle capability of the model, i. e., how far can it generate unseen semantics (e. g., classes, attributes, and styles) onto a given layout, and call the task Freestyle LIS (FLIS).
1 code implementation • CVPR 2023 • Yi Zhang, Xiaoyang Huang, Bingbing Ni, Teng Li, Wenjun Zhang
We develop an effective point cloud rendering pipeline for novel view synthesis, which enables high fidelity local detail reconstruction, real-time rendering and user-friendly editing.
no code implementations • 21 Feb 2023 • Yue Shi, Yuxuan Xiong, Jingyi Chai, Bingbing Ni, Wenjun Zhang
To address these issues, we propose an unsupervised separated 3D garments and human reconstruction model (USR), which reconstructs the human body and authentic textured clothes in layers without 3D models.
1 code implementation • 30 Jan 2023 • Xiaoyang Huang, Yanjun Wang, Yang Liu, Bingbing Ni, Wenjun Zhang, Jinxian Liu, Teng Li
To this end, we propose to achieve personalized spatial audio by reconstructing 3D human ears with single-view images.
1 code implementation • ICCV 2023 • Xiaoyang Huang, Yi Zhang, Kai Chen, Teng Li, Wenjun Zhang, Bingbing Ni
In this work, a novel regularization term named Implicit Convexity Regularization (ICR) imposed on implicit primitive learning is proposed to tackle this problem.
no code implementations • 5 Dec 2022 • Yue Shi, Dingyi Rong, Bingbing Ni, Chang Chen, Wenjun Zhang
To address these issues, we propose Geometry-Aware Generalized Neural Radiance Field (GARF) with a geometry-aware dynamic sampling (GADS) strategy to perform real-time novel view rendering and unsupervised depth estimation on unseen scenes without per-scene optimization.
1 code implementation • 27 Oct 2022 • Xiaoyang Huang, Yi Zhang, Bingbing Ni, Teng Li, Kai Chen, Wenjun Zhang
In this work, we focus on boosting the image quality of point clouds rendering with a compact model design.
no code implementations • 22 Aug 2022 • Shunli Ren, Siheng Chen, Wenjun Zhang
Perception is one of the crucial module of the autonomous driving system, which has made great progress recently.
1 code implementation • 18 Jul 2022 • Zixing Lei, Shunli Ren, Yue Hu, Wenjun Zhang, Siheng Chen
Collaborative perception has recently shown great potential to improve perception capabilities over single-agent perception.
no code implementations • 5 Jul 2022 • Runnan Liu, Liang Liu, Dazhi He, Wenjun Zhang, Erik G. Larsson
Our paper aims to adopt the classic change detection theory to detect the change in the channel covariance matrix as accurately and quickly as possible such that the new covariance matrix can be re-estimated in time.
no code implementations • 1 May 2022 • Jiling Cao, Jeong-Hoon Kim, Xi Li, Wenjun Zhang
In this paper, we derive closed-form formulas of first-order approximation for down-and-out barrier and floating strike lookback put option prices under a stochastic volatility model, by using an asymptotic approach.
no code implementations • 22 Mar 2022 • Kai Song, Biqian Feng, Yongpeng Wu, Wenjun Zhang
Finally, with our work, a PLC network based on E-PMAC mechanism can be realized.
2 code implementations • CVPR 2022 • Chenxin Xu, Weibo Mao, Wenjun Zhang, Siheng Chen
However, in this way, the model parameters come from all seen instances, which means a huge amount of irrelevant seen instances might also involve in predicting the current situation, disturbing the performance.
Ranked #6 on Trajectory Prediction on Stanford Drone
1 code implementation • ICLR 2022 • Xiaoyang Huang, Jiancheng Yang, Yanjun Wang, Ziyu Chen, Linguo Li, Teng Li, Bingbing Ni, Wenjun Zhang
In this study, we present Representation-Agnostic Shape Fields (RASF), a generalizable and computation-efficient shape embedding module for 3D deep learning.
no code implementations • 16 Mar 2022 • Zefan Li, Bingbing Ni, Teng Li, Wenjun Zhang, Wen Gao
GCGD consists of two plug-in modules: 1) inspired by the idea of gradient prediction, we propose a \textbf{GC-W} module for weight gradient correction; 2) based on Neural ODE, we propose a \textbf{GC-ODE} module for hidden states gradient correction.
no code implementations • 26 Feb 2022 • Boxiao Shen, Yongpeng Wu, Jianping An, Chengwen Xing, Lian Zhao, Wenjun Zhang
Next, by exploring the sparsity of channel in the delay-Doppler-angle domain, a two-dimensional pattern coupled hierarchical prior with the sparse Bayesian learning and covariance-free method (TDSBL-CF) is developed for the channel estimation.
2 code implementations • NeurIPS 2021 • Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng, Wenjun Zhang
Our approach is validated on V2X-Sim 1. 0, a large-scale multi-agent perception dataset that we synthesized using CARLA and SUMO co-simulation.
Ranked #4 on 3D Object Detection on V2XSet
1 code implementation • 9 Sep 2021 • Runnan Liu, Liang Liu, Dazhi He, Wenjun Zhang, Erik G. Larsson
This result verifies the possibility to detect the channel covariance change both accurately and quickly in practice.
no code implementations • CVPR 2021 • Zefan Li, Chenxi Liu, Alan Yuille, Bingbing Ni, Wenjun Zhang, Wen Gao
For a given unsupervised task, we design multilevel tasks and define different learning stages for the deep network.
1 code implementation • CVPR 2021 • Linguo Li, Minsi Wang, Bingbing Ni, Hang Wang, Jiancheng Yang, Wenjun Zhang
In this work, we propose a Cross-view Contrastive Learning framework for unsupervised 3D skeleton-based action Representation (CrosSCLR), by leveraging multi-view complementary supervision signal.
5 code implementations • 29 Mar 2021 • Yuncong Li, Fang Wang, Wenjun Zhang, Sheng-hua Zhong, Cunxiang Yin, Yancheng He
Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences and tries to provide a complete solution for aspect-based sentiment analysis (ABSA).
Ranked #1 on Aspect-Sentiment-Opinion Triplet Extraction on Res14
Aspect-Based Sentiment Analysis Aspect-Sentiment-Opinion Triplet Extraction +2
no code implementations • ICCV 2021 • Zhenbo Yu, Junjie Wang, Jingwei Xu, Bingbing Ni, Chenglong Zhao, Minsi Wang, Wenjun Zhang
The challenges of the latter task are two folds: (1) pose failure (i. e., pose mismatching -- different skeleton definitions in dataset and SMPL , and pose ambiguity -- endpoints have arbitrary joint angle configurations for the same 3D joint coordinates).
no code implementations • ICCV 2021 • Yue Shi, Bingbing Ni, Jinxian Liu, Dingyi Rong, Ye Qian, Wenjun Zhang
Pixel-to-mesh has wide applications, especially in virtual or augmented reality, animation and game industry.
no code implementations • ICCV 2021 • Zhenbo Yu, Bingbing Ni, Jingwei Xu, Junjie Wang, Chenglong Zhao, Wenjun Zhang
Furthermore, two temporal constraints are proposed to alleviate the scale and pose ambiguity respectively.
Monocular 3D Human Pose Estimation Unsupervised 3D Human Pose Estimation
no code implementations • 1 Jan 2021 • Minghao Xu, Hang Wang, Bingbing Ni, Wenjun Zhang, Jian Tang
We propose to disentangle graph structure and node attributes into two distinct sets of representations, and such disentanglement can be done in either the input or the embedding space.
1 code implementation • ECCV 2020 • Hang Wang, Minghao Xu, Bingbing Ni, Wenjun Zhang
Transferring knowledges learned from multiple source domains to target domain is a more practical and challenging task than conventional single-source domain adaptation.
Domain Adaptation Multi-Source Unsupervised Domain Adaptation
1 code implementation • CVPR 2020 • Minghao Xu, Hang Wang, Bingbing Ni, Qi Tian, Wenjun Zhang
To mitigate these problems, we propose a Graph-induced Prototype Alignment (GPA) framework to seek for category-level domain alignment via elaborate prototype representations.
no code implementations • 12 Dec 2019 • Yucheng Zhu, Xiongkuo Min, Dandan Zhu, Ke Gu, Jiantao Zhou, Guangtao Zhai, Xiaokang Yang, Wenjun Zhang
The saliency annotations of head and eye movements for both original and augmented videos are collected and together constitute the ARVR dataset.
1 code implementation • 4 Dec 2019 • Minghao Xu, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, Wenjun Zhang
In this paper, we present adversarial domain adaptation with domain mixup (DM-ADA), which guarantees domain-invariance in a more continuous latent space and guides the domain discriminator in judging samples' difference relative to source and target domains.
no code implementations • 6 Apr 2019 • Muming Zhao, Jian Zhang, Chongyang Zhang, Wenjun Zhang
Towards this problem, in this paper we propose a constrained multi-stage Convolutional Neural Networks (CNNs) to jointly pursue locally consistent density map from two aspects.
1 code implementation • ECCV 2018 • Ji Zhu, Hua Yang, Nian Liu, Minyoung Kim, Wenjun Zhang, Ming-Hsuan Yang
In this paper, we propose an online Multi-Object Tracking (MOT) approach which integrates the merits of single object tracking and data association methods in a unified framework to handle noisy detections and frequent interactions between targets.
Ranked #5 on Online Multi-Object Tracking on MOT16
no code implementations • 20 Apr 2018 • Shiyu Ning, Hongteng Xu, Li Song, Rong Xie, Wenjun Zhang
Transferring a low-dynamic-range (LDR) image to a high-dynamic-range (HDR) image, which is the so-called inverse tone mapping (iTM), is an important imaging technique to improve visual effects of imaging devices.
no code implementations • ECCV 2018 • Yan Wang, Lingxi Xie, Siyuan Qiao, Ya zhang, Wenjun Zhang, Alan L. Yuille
Convolution is spatially-symmetric, i. e., the visual features are independent of its position in the image, which limits its ability to utilize contextual cues for visual recognition.
no code implementations • ICCV 2017 • Zefan Li, Bingbing Ni, Wenjun Zhang, Xiaokang Yang, Wen Gao
Input binarization has shown to be an effective way for network acceleration.
no code implementations • ICCV 2017 • Yan Wang, Lingxi Xie, Chenxi Liu, Ya zhang, Wenjun Zhang, Alan Yuille
In this paper, we reveal the importance and benefits of introducing second-order operations into deep neural networks.
no code implementations • 3 Mar 2017 • Yan Wang, Lingxi Xie, Ya zhang, Wenjun Zhang, Alan Yuille
We formulate the function of a convolutional layer as learning a large visual vocabulary, and propose an alternative way, namely Deep Collaborative Learning (DCL), to reduce the computational complexity.
no code implementations • 30 Oct 2016 • Rory P. Bunker, Wenjun Zhang, M. Asif Naeem
In this paper, we investigate the extent to which features derived from bank statements provided by loan applicants, and which are not declared on an application form, can enhance a credit scoring model for a New Zealand lending company.
no code implementations • 30 Oct 2016 • Teh Raihana Nazirah Roslan, Wenjun Zhang, Jiling Cao
This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization.