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Zhihao Gu's Projects

paddlevit icon paddlevit

:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+

plot icon plot

[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models

point-bert icon point-bert

[CVPR 2022] Pre-Training 3D Point Cloud Transformers with Masked Point Modeling

point-mae icon point-mae

[ECCV2022] Masked Autoencoders for Point Cloud Self-supervised Learning

pointclip_v2 icon pointclip_v2

[ICCV 2023] PointCLIP V2: Adapting CLIP for Powerful 3D Open-world Learning

pointcmt icon pointcmt

[NeurIPS2022] Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis

pointllm icon pointllm

[arXiv 2023] PointLLM: Empowering Large Language Models to Understand Point Clouds

ps-vit icon ps-vit

Official implementation of the paper Vision Transformer with Progressive Sampling, ICCV 2021.

psconv icon psconv

[ECCV 2020] PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer

pysot icon pysot

SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.

pytorch-image-models icon pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-video-understanding icon pytorch-video-understanding

This codebase will provide a comprehensive video understanding solution, including state-of-the-art video models (both convolutional and transformer-based), self-supervised video representation learning approaches and temporal action detection methods, etc.

pytorchvideo icon pytorchvideo

A deep learning library for video understanding research.

rasnet icon rasnet

Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking

rd4ad icon rd4ad

Anomaly Detection via Reverse Distillation from One-Class Embedding

rdd icon rdd

Realtime Deepfake Detection

reb icon reb

REB:Reducing Biases in Representation for Industrial Anomaly Detection

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