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20162024
most citedSkeleton-based Action Recognition with Convolutional Neural Networks

284 citations · 637 across the 43 of their papers we have counts for

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Showing 2022Show all

13 papers · 1 filter

cs.CV2022★ 3 cited

NeRF-Gaze: A Head-Eye Redirection Parametric Model for Gaze Estimation

Pengwei Yin, Jiawu Dai, Jingjing Wang +2

Gaze estimation is the fundamental basis for many visual tasks. Yet, the high cost of acquiring gaze datasets with 3D annotations hinders the optimization and application of gaze e…

cs.CV2022★ 3 cited

Attention Diversification for Domain Generalization

Rang Meng, Xianfeng Li, Weijie Chen +7

Convolutional neural networks (CNNs) have demonstrated gratifying results at learning discriminative features. However, when applied to unseen domains, state-of-the-art models are…

cs.CV2022★ 1 cited

FBNet: Feedback Network for Point Cloud Completion

Xuejun Yan, Hongyu Yan, Jingjing Wang +5

The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedfo…

cs.CV2022★ 7 cited

Point Cloud Upsampling via Cascaded Refinement Network

Hang Du, Xuejun Yan, Jingjing Wang +2

Point cloud upsampling focuses on generating a dense, uniform and proximity-to-surface point set. Most previous approaches accomplish these objectives by carefully designing a sing…

cs.CV2022★ 1 cited

Multi-Scale Wavelet Transformer for Face Forgery Detection

Jie Liu, Jingjing Wang, Peng Zhang +3

Currently, many face forgery detection methods aggregate spatial and frequency features to enhance the generalization ability and gain promising performance under the cross-dataset…

cs.CV2022

Semi-supervised Ranking for Object Image Blur Assessment

Qiang Li, Zhaoliang Yao, Jingjing Wang +4

Assessing the blurriness of an object image is fundamentally important to improve the performance for object recognition and retrieval. The main challenge lies in the lack of abund…

cs.CV2022

Slimmable Domain Adaptation

Rang Meng, Weijie Chen, Shicai Yang +7

Vanilla unsupervised domain adaptation methods tend to optimize the model with fixed neural architecture, which is not very practical in real-world scenarios since the target data…

cs.CV2022★ 3 cited

Label Matching Semi-Supervised Object Detection

Binbin Chen, Weijie Chen, Shicai Yang +6

Semi-supervised object detection has made significant progress with the development of mean teacher driven self-training. Despite the promising results, the label mismatch problem…

cs.CV2022★ 33 cited

Learning Domain Adaptive Object Detection with Probabilistic Teacher

Meilin Chen, Weijie Chen, Shicai Yang +8

Self-training for unsupervised domain adaptive object detection is a challenging task, of which the performance depends heavily on the quality of pseudo boxes. Despite the promisin…

cs.CV2022

Transductive CLIP with Class-Conditional Contrastive Learning

Junchu Huang, Weijie Chen, Shicai Yang +3

Inspired by the remarkable zero-shot generalization capacity of vision-language pre-trained model, we seek to leverage the supervision from CLIP model to alleviate the burden of da…

cs.CV2022★ 1 cited

2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach

Yilu Guo, Shicai Yang, Weijie Chen +3

Convolutional neural networks (CNNs) have achieved significant success in image classification by utilizing large-scale datasets. However, it is still of great challenge to learn f…

cs.LG2022

KRNet: Towards Efficient Knowledge Replay

Yingying Zhang, Qiaoyong Zhong, Di Xie +1

The knowledge replay technique has been widely used in many tasks such as continual learning and continuous domain adaptation. The key lies in how to effectively encode the knowled…

cs.CV2022

Self-distilled Knowledge Delegator for Exemplar-free Class Incremental Learning

Fanfan Ye, Liang Ma, Qiaoyong Zhong +2

Exemplar-free incremental learning is extremely challenging due to inaccessibility of data from old tasks. In this paper, we attempt to exploit the knowledge encoded in a previousl…