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Type: User
Company: Peking University
Bio: Visual Data Interpreting and Generation Lab
Type: User
Company: Peking University
Bio: Visual Data Interpreting and Generation Lab
[AAAI 2024] BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios
Composite Backbone Network (AAAI20)
CBNet implementation based on mmdetection (AAAI 2020)
[TIP 2022] CBNetV2: A Composite Backbone Network Architecture for Object Detection
Comprehensive Feature Enhancement Module for Single-Shot Object Detector
[AAAI 2022] CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes
[ICME 2022] Continual Contrastive Learning for Image Classification
[ECCV 2020] DADA: Differentiable Automatic Data Augmentation
[CVPR 2024] DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes
[CVPR 2023] DynamicDet: A Unified Dynamic Architecture for Object Detection
[IJCV 2023] FlowNAS: Neural Architecture Search for Optical Flow Estimation
[WACV 2023] Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers
[ICML 2024] GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
official implementation of paper: GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling
[ECCV 2024] HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
[CVPR 2021]OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection
Learning a Single Model With a Wide Range of Quality Factors for JPEG Image Artifacts Removal (TIP 2020)
[CVPR 2024] RCBEVDet: Radar-camera Fusion in Bird’s Eye View for 3D Object Detection
(ICME2021) RPATTACK: REFINED PATCH ATTACK ON GENERAL OBJECT DETECTORS
[ICCV 2023] SAMPLING: Scene-adaptive Hierarchical Multiplane Images Representation for Novel View Synthesis from a Single Image
[CVPR 2023] T-SEA: Transfer-based Self-Ensemble Attack on Object Detection
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