Wenxiao Wang

Orcid: 0000-0002-6399-292X

Affiliations:
  • Zhejiang University, Hangzhou, China


According to our database1, Wenxiao Wang authored at least 36 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation.
IEEE Trans. Circuits Syst. Video Technol., January, 2024

Model Compression and Efficient Inference for Large Language Models: A Survey.
CoRR, 2024

Regulating Intermediate 3D Features for Vision-Centric Autonomous Driving.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detection.
IEEE Trans. Image Process., 2023

To be or not to be? an exploration of continuously controllable prompt engineering.
CoRR, 2023

Few-shot Hybrid Domain Adaptation of Image Generators.
CoRR, 2023

M<sup>3</sup>CS: Multi-Target Masked Point Modeling with Learnable Codebook and Siamese Decoders.
CoRR, 2023

MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection.
CoRR, 2023

A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation.
CoRR, 2023

SelFLoc: Selective Feature Fusion for Large-scale Point Cloud-based Place Recognition.
CoRR, 2023

Learning Occupancy for Monocular 3D Object Detection.
CoRR, 2023

Img2Vec: A Teacher of High Token-Diversity Helps Masked AutoEncoders.
CoRR, 2023

APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding.
CoRR, 2023

Neural Collapse Inspired Federated Learning with Non-iid Data.
CoRR, 2023

CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale Attention.
CoRR, 2023

General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment.
CoRR, 2023

MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

One-shot Implicit Animatable Avatars with Model-based Priors.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Towards In-Distribution Compatible Out-of-Distribution Detection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Toward Better Accuracy-Efficiency Trade-Offs: Divide and Co-Training.
IEEE Trans. Image Process., 2022

OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detection.
CoRR, 2022

Towards In-distribution Compatibility in Out-of-distribution Detection.
CoRR, 2022

Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation.
CoRR, 2022

CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph.
Proceedings of the Computer Vision - ECCV 2022, 2022

Masked Autoencoders for Point Cloud Self-supervised Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
COP: customized correlation-based Filter level pruning method for deep CNN compression.
Neurocomputing, 2021

CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention.
CoRR, 2021

Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
SplitNet: Divide and Co-training.
CoRR, 2020

Accelerate Your CNN from Three Dimensions: A Comprehensive Pruning Framework.
CoRR, 2020

Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds.
CoRR, 2020

2019
DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration.
CoRR, 2019

COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019


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