Search Results for author: Wenxi Liu

Found 29 papers, 11 papers with code

Beyond Night Visibility: Adaptive Multi-Scale Fusion of Infrared and Visible Images

no code implementations2 Mar 2024 Shufan Pei, Junhong Lin, Wenxi Liu, Tiesong Zhao, Chia-Wen Lin

Thereby, we obtain an image free of low light and light effects, which improves the performance of nighttime object detection.

object-detection Object Detection

Distractor-aware Event-based Tracking

no code implementations22 Oct 2023 Yingkai Fu, Meng Li, Wenxi Liu, Yuanchen Wang, Jiqing Zhang, BaoCai Yin, Xiaopeng Wei, Xin Yang

We demonstrate that our tracker has superior performance against the state-of-the-art trackers in terms of both accuracy and efficiency.

Object Visual Object Tracking

Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery

no code implementations7 Oct 2023 Qi Li, Jiaxin Cai, Yuanlong Yu, Jason Gu, Jia Pan, Wenxi Liu

Within the domain of UAV imagery analysis, the segmentation of ultra-high resolution images emerges as a substantial and intricate challenge, especially when grappling with the constraints imposed by GPU memory-restricted computational devices.

Segmentation Semantic Segmentation

Frame-Event Alignment and Fusion Network for High Frame Rate Tracking

1 code implementation CVPR 2023 Jiqing Zhang, Yuanchen Wang, Wenxi Liu, Meng Li, Jinpeng Bai, BaoCai Yin, Xin Yang

The alignment module is responsible for cross-style and cross-frame-rate alignment between frame and event modalities under the guidance of the moving cues furnished by events.

Object Tracking

Single-View View Synthesis with Self-Rectified Pseudo-Stereo

no code implementations19 Apr 2023 Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He

In this way, the challenging novel view synthesis process is decoupled into two simpler problems of stereo synthesis and 3D reconstruction.

3D Reconstruction Novel View Synthesis

Diffuse3D: Wide-Angle 3D Photography via Bilateral Diffusion

1 code implementation ICCV 2023 Yutao Jiang, Yang Zhou, Yuan Liang, Wenxi Liu, Jianbo Jiao, Yuhui Quan, Shengfeng He

To address the above issues, we propose Diffuse3D which employs a pre-trained diffusion model for global synthesis, while amending the model to activate depth-aware inference.

Denoising Novel View Synthesis

Monocular BEV Perception of Road Scenes via Front-to-Top View Projection

no code implementations15 Nov 2022 Wenxi Liu, Qi Li, Weixiang Yang, Jiaxin Cai, Yuanlong Yu, Yuexin Ma, Shengfeng He, Jia Pan

We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen the view transformation and scene understanding.

Autonomous Driving Road Segmentation +1

Glance to Count: Learning to Rank with Anchors for Weakly-supervised Crowd Counting

no code implementations29 May 2022 Zheng Xiong, Liangyu Chai, Wenxi Liu, Yongtuo Liu, Sucheng Ren, Shengfeng He

To enable training under this new setting, we convert the crowd count regression problem to a ranking potential prediction problem.

Crowd Counting Learning-To-Rank

End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Maps

1 code implementation CVPR 2022 Ke Guo, Wenxi Liu, Jia Pan

In this paper, we aim to forecast a future trajectory distribution of a moving agent in the real world, given the social scene images and historical trajectories.

Trajectory Prediction

Semi-Supervised Domain Generalization with Evolving Intermediate Domain

1 code implementation19 Nov 2021 Luojun Lin, Han Xie, Zhishu Sun, WeiJie Chen, Wenxi Liu, Yuanlong Yu, Lei Zhang

From this perspective, we introduce a novel paradigm of DG, termed as Semi-Supervised Domain Generalization (SSDG), to explore how the labeled and unlabeled source domains can interact, and establish two settings, including the close-set and open-set SSDG.

Domain Generalization Semi-Supervised Domain Generalization

Ultra-high Resolution Image Segmentation via Locality-aware Context Fusion and Alternating Local Enhancement

1 code implementation ICCV 2021 Wenxi Liu, Qi Li, Xindai Lin, Weixiang Yang, Shengfeng He, Yuanlong Yu

In particular, we introduce a novel locality-aware context fusion based segmentation model to process local patches, where the relevance between local patch and its various contexts are jointly and complementarily utilized to handle the semantic regions with large variations.

Image Segmentation Land Cover Classification +2

Reciprocal Transformations for Unsupervised Video Object Segmentation

1 code implementation CVPR 2021 Sucheng Ren, Wenxi Liu, Yongtuo Liu, Haoxin Chen, Guoqiang Han, Shengfeng He

Additionally, to exclude the information of the moving background objects from motion features, our transformation module enables to reciprocally transform the appearance features to enhance the motion features, so as to focus on the moving objects with salient appearance while removing the co-moving outliers.

Object Optical Flow Estimation +3

Coarse-To-Fine Person Re-Identification With Auxiliary-Domain Classification and Second-Order Information Bottleneck

no code implementations CVPR 2021 Anguo Zhang, Yueming Gao, Yuzhen Niu, Wenxi Liu, Yongcheng Zhou

Person re-identification (Re-ID) is to retrieve a particular person captured by different cameras, which is of great significance for security surveillance and pedestrian behavior analysis.

domain classification Miscellaneous +1

An Intelligent CNN-VAE Text Representation Technology Based on Text Semantics for Comprehensive Big Data

no code implementations28 Aug 2020 Genggeng Liu, Canyang Guo, Lin Xie, Wenxi Liu, Naixue Xiong, Guolong Chen

CNN is used to extract the features of text vector to get the semantics among words and VAE is introduced to make the text feature space more consistent with Gaussian distribution.

text-classification Text Classification

Mapping in a cycle: Sinkhorn regularized unsupervised learning for point cloud shapes

1 code implementation ECCV 2020 Lei Yang, Wenxi Liu, Zhiming Cui, Nenglun Chen, Wenping Wang

We propose an unsupervised learning framework with the pretext task of finding dense correspondences between point cloud shapes from the same category based on the cycle-consistency formulation.

HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions

1 code implementation3 Jul 2020 Yuzhen Niu, Jianbin Wu, Wenxi Liu, Wenzhong Guo, Rynson W. H. Lau

To address these two problems, we propose in this paper a novel GAN-based model, HDR-GAN, for synthesizing HDR images from multi-exposed LDR images.

HDR Reconstruction Image Reconstruction

Recurrent Distillation based Crowd Counting

no code implementations14 Jun 2020 Yue Gu, Wenxi Liu

Besides, leveraging our density map generation method, we propose an iterative distillation algorithm to progressively enhance our model with identical network structures, without significantly sacrificing the dimension of the output density maps.

Crowd Counting

Over-crowdedness Alert! Forecasting the Future Crowd Distribution

no code implementations9 Jun 2020 Yuzhen Niu, Weifeng Shi, Wenxi Liu, Shengfeng He, Jia Pan, Antoni B. Chan

In this paper, we formulate a novel crowd analysis problem, in which we aim to predict the crowd distribution in the near future given sequential frames of a crowd video without any identity annotations.

Learning Resilient Behaviors for Navigation Under Uncertainty

no code implementations22 Oct 2019 Tingxiang Fan, Pinxin Long, Wenxi Liu, Jia Pan, Ruigang Yang, Dinesh Manocha

Deep reinforcement learning has great potential to acquire complex, adaptive behaviors for autonomous agents automatically.

Autonomous Driving

Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery

no code implementations ICCV 2019 Xiaosheng Yan, Yuanlong Yu, Feigege Wang, Wenxi Liu, Shengfeng He, Jia Pan

We conduct comparison experiments on this dataset and demonstrate that our model outperforms the state-of-the-art in tasks of recovering segmentation mask and appearance for occluded vehicles.


Enhancement Mask for Hippocampus Detection and Segmentation

no code implementations12 Feb 2019 Dengsheng Chen, Wenxi Liu, You Huang, Tong Tong, Yuanlong Yu

Detection and segmentation of the hippocampal structures in volumetric brain images is a challenging problem in the area of medical imaging.

Hippocampus Segmentation

Deformable Object Tracking with Gated Fusion

no code implementations27 Sep 2018 Wenxi Liu, Yibing Song, Dengsheng Chen, Shengfeng He, Yuanlong Yu, Tao Yan, Gerhard P. Hancke, Rynson W. H. Lau

In addition, we also propose a gated fusion scheme to control how the variations captured by the deformable convolution affect the original appearance.

Object Object Tracking

An Intelligent Extraversion Analysis Scheme from Crowd Trajectories for Surveillance

no code implementations27 Sep 2018 Wenxi Liu, Yuanlong Yu, Chun-Yang Zhang, Genggeng Liu, Naixue Xiong

To our best knowledge, this is the first attempt to analyze individual extraversion of crowd motions based on trajectories.

Active Learning Attribute +2

Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning

2 code implementations28 Sep 2017 Pinxin Long, Tingxiang Fan, Xinyi Liao, Wenxi Liu, Hao Zhang, Jia Pan

We validate the learned sensor-level collision avoidance policy in a variety of simulated scenarios with thorough performance evaluations and show that the final learned policy is able to find time efficient, collision-free paths for a large-scale robot system.

Collision Avoidance reinforcement-learning +1

Deep-Learned Collision Avoidance Policy for Distributed Multi-Agent Navigation

no code implementations22 Sep 2016 Pinxin Long, Wenxi Liu, Jia Pan

We validate the learned deep neural network policy in a set of simulated and real scenarios with noisy measurements and demonstrate that our method is able to generate a robust navigation strategy that is insensitive to imperfect sensing and works reliably in all situations.

Collision Avoidance

Exemplar-AMMs: Recognizing Crowd Movements from Pedestrian Trajectories

no code implementations31 Mar 2016 Wenxi Liu, Rynson W. H. Lau, Xiaogang Wang, Dinesh Manocha

Specifically, we propose an optimization framework that filters out the unknown noise in the crowd trajectories and measures their similarity to the exemplar-AMMs to produce a crowd motion feature.

Multi-Label Classification

Leveraging Long-Term Predictions and Online-Learning in Agent-based Multiple Person Tracking

no code implementations10 Feb 2014 Wenxi Liu, Antoni B. Chan, Rynson W. H. Lau, Dinesh Manocha

We present a multiple-person tracking algorithm, based on combining particle filters and RVO, an agent-based crowd model that infers collision-free velocities so as to predict pedestrian's motion.


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