Search Results for author: Yingwei Li

Found 27 papers, 17 papers with code

Point Cloud Self-supervised Learning via 3D to Multi-view Masked Autoencoder

1 code implementation17 Nov 2023 Zhimin Chen, Yingwei Li, Longlong Jing, Liang Yang, Bing Li

However, a notable limitation of these approaches is that they do not fully utilize the multi-view attributes inherent in 3D point clouds, which is crucial for a deeper understanding of 3D structures.

3D Object Classification 3D Object Detection +3

MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences

1 code implementation CVPR 2023 Yingwei Li, Charles R. Qi, Yin Zhou, Chenxi Liu, Dragomir Anguelov

The MoDAR modality propagates object information from temporal contexts to a target frame, represented as a set of virtual points, one for each object from a waypoint on a forecasted trajectory.

3D Object Detection Motion Forecasting +1

Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models

1 code implementation NeurIPS 2023 Zhimin Chen, Longlong Jing, Yingwei Li, Bing Li

Foundation models have achieved remarkable results in 2D and language tasks like image segmentation, object detection, and visual-language understanding.

3D Object Detection Image Captioning +6

AsyInst: Asymmetric Affinity with DepthGrad and Color for Box-Supervised Instance Segmentation

no code implementations7 Dec 2022 Siwei Yang, Longlong Jing, Junfei Xiao, Hang Zhao, Alan Yuille, Yingwei Li

Through systematic analysis, we found that the commonly used pairwise affinity loss has two limitations: (1) it works with color affinity but leads to inferior performance with other modalities such as depth gradient, (2)the original affinity loss does not prevent trivial predictions as intended but actually accelerates this process due to the affinity loss term being symmetric.

Box-supervised Instance Segmentation Segmentation +2

Context-Enhanced Stereo Transformer

1 code implementation21 Oct 2022 Weiyu Guo, Zhaoshuo Li, Yongkui Yang, Zheng Wang, Russell H. Taylor, Mathias Unberath, Alan Yuille, Yingwei Li

We construct our stereo depth estimation model, Context Enhanced Stereo Transformer (CSTR), by plugging CEP into the state-of-the-art stereo depth estimation method Stereo Transformer.

Stereo Depth Estimation Stereo Matching

Class-Level Confidence Based 3D Semi-Supervised Learning

1 code implementation18 Oct 2022 Zhimin Chen, Longlong Jing, Liang Yang, Yingwei Li, Bing Li

Firstly, a dynamic thresholding strategy is proposed to utilize more unlabeled data, especially for low learning status classes.

Fast AdvProp

1 code implementation ICLR 2022 Jieru Mei, Yucheng Han, Yutong Bai, Yixiao Zhang, Yingwei Li, Xianhang Li, Alan Yuille, Cihang Xie

Specifically, our modifications in Fast AdvProp are guided by the hypothesis that disentangled learning with adversarial examples is the key for performance improvements, while other training recipes (e. g., paired clean and adversarial training samples, multi-step adversarial attackers) could be largely simplified.

Data Augmentation object-detection +1

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

1 code implementation CVPR 2022 Yingwei Li, Adams Wei Yu, Tianjian Meng, Ben Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Bo Wu, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan Yuille, Mingxing Tan

In this paper, we propose two novel techniques: InverseAug that inverses geometric-related augmentations, e. g., rotation, to enable accurate geometric alignment between lidar points and image pixels, and LearnableAlign that leverages cross-attention to dynamically capture the correlations between image and lidar features during fusion.

3D Object Detection Autonomous Driving +2

Learning from Temporal Gradient for Semi-supervised Action Recognition

1 code implementation CVPR 2022 Junfei Xiao, Longlong Jing, Lin Zhang, Ju He, Qi She, Zongwei Zhou, Alan Yuille, Yingwei Li

Our method achieves the state-of-the-art performance on three video action recognition benchmarks (i. e., Kinetics-400, UCF-101, and HMDB-51) under several typical semi-supervised settings (i. e., different ratios of labeled data).

Action Recognition Temporal Action Localization

Searching for TrioNet: Combining Convolution with Local and Global Self-Attention

no code implementations15 Nov 2021 Huaijin Pi, Huiyu Wang, Yingwei Li, Zizhang Li, Alan Yuille

In order to effectively search in this huge architecture space, we propose Hierarchical Sampling for better training of the supernet.

Neural Architecture Search

Harnessing Perceptual Adversarial Patches for Crowd Counting

1 code implementation16 Sep 2021 Shunchang Liu, Jiakai Wang, Aishan Liu, Yingwei Li, Yijie Gao, Xianglong Liu, DaCheng Tao

Crowd counting, which has been widely adopted for estimating the number of people in safety-critical scenes, is shown to be vulnerable to adversarial examples in the physical world (e. g., adversarial patches).

Crowd Counting

Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples

no code implementations29 Oct 2020 Yingwei Li, Zhuotun Zhu, Yuyin Zhou, Yingda Xia, Wei Shen, Elliot K. Fishman, Alan L. Yuille

Although deep neural networks have been a dominant method for many 2D vision tasks, it is still challenging to apply them to 3D tasks, such as medical image segmentation, due to the limited amount of annotated 3D data and limited computational resources.

Image Segmentation Pancreas Segmentation +2

Shape-Texture Debiased Neural Network Training

1 code implementation ICLR 2021 Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie

To prevent models from exclusively attending on a single cue in representation learning, we augment training data with images with conflicting shape and texture information (eg, an image of chimpanzee shape but with lemon texture) and, most importantly, provide the corresponding supervisions from shape and texture simultaneously.

Adversarial Robustness Data Augmentation +2

Neural Architecture Search for Lightweight Non-Local Networks

2 code implementations CVPR 2020 Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, Alan Yuille

However, it has been rarely explored to embed the NL blocks in mobile neural networks, mainly due to the following challenges: 1) NL blocks generally have heavy computation cost which makes it difficult to be applied in applications where computational resources are limited, and 2) it is an open problem to discover an optimal configuration to embed NL blocks into mobile neural networks.

Image Classification Neural Architecture Search

CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks

1 code implementation28 Mar 2020 Qihang Yu, Yingwei Li, Jieru Mei, Yuyin Zhou, Alan L. Yuille

3D Convolution Neural Networks (CNNs) have been widely applied to 3D scene understanding, such as video analysis and volumetric image recognition.

3D Medical Imaging Segmentation Action Recognition +3

Adversarial Attacks on Monocular Depth Estimation

no code implementations23 Mar 2020 Ziqi Zhang, Xinge Zhu, Yingwei Li, Xiangqun Chen, Yao Guo

In order to understand the impact of adversarial attacks on depth estimation, we first define a taxonomy of different attack scenarios for depth estimation, including non-targeted attacks, targeted attacks and universal attacks.

Autonomous Driving Monocular Depth Estimation +3

AtomNAS: Fine-Grained End-to-End Neural Architecture Search

1 code implementation ICLR 2020 Jieru Mei, Yingwei Li, Xiaochen Lian, Xiaojie Jin, Linjie Yang, Alan Yuille, Jianchao Yang

We propose a fine-grained search space comprised of atomic blocks, a minimal search unit that is much smaller than the ones used in recent NAS algorithms.

Neural Architecture Search

Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation

no code implementations3 Sep 2019 Yuyin Zhou, Yingwei Li, Zhishuai Zhang, Yan Wang, Angtian Wang, Elliot Fishman, Alan Yuille, Seyoun Park

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with an overall five-year survival rate of 8%.

Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures

no code implementations23 Jun 2019 Yuyin Zhou, David Dreizin, Yingwei Li, Zhishuai Zhang, Yan Wang, Alan Yuille

Trauma is the worldwide leading cause of death and disability in those younger than 45 years, and pelvic fractures are a major source of morbidity and mortality.


Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses

1 code implementation ECCV 2020 Yingwei Li, Song Bai, Cihang Xie, Zhenyu Liao, Xiaohui Shen, Alan L. Yuille

We observe the property of regional homogeneity in adversarial perturbations and suggest that the defenses are less robust to regionally homogeneous perturbations.

object-detection Object Detection +1

Adversarial Metric Attack and Defense for Person Re-identification

1 code implementation30 Jan 2019 Song Bai, Yingwei Li, Yuyin Zhou, Qizhu Li, Philip H. S. Torr

However, our work observes the extreme vulnerability of existing distance metrics to adversarial examples, generated by simply adding human-imperceptible perturbations to person images.

Adversarial Attack Benchmarking +2

Learning Transferable Adversarial Examples via Ghost Networks

1 code implementation9 Dec 2018 Yingwei Li, Song Bai, Yuyin Zhou, Cihang Xie, Zhishuai Zhang, Alan Yuille

The critical principle of ghost networks is to apply feature-level perturbations to an existing model to potentially create a huge set of diverse models.

Adversarial Attack

VLAD3: Encoding Dynamics of Deep Features for Action Recognition

no code implementations CVPR 2016 Yingwei Li, Weixin Li, Vijay Mahadevan, Nuno Vasconcelos

To account for long-range inhomogeneous dynamics, a VLAD descriptor is derived for the LDS and pooled over the whole video, to arrive at the final VLAD^3 representation.

Action Recognition Temporal Action Localization

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