Bo Zhang (BOBrown)

BOBrown

Geek Repo

Company:Shanghai AI Laboratory

Location:Shanghai ,China

Home Page:https://bobrown.github.io/boZhang.github.io/

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Bo Zhang's repositories

CCDA_LGFA

Curriculum-style Local-to-global Adaptation for Cross-domain Remote Sensing Image Segmentation

Deeparsing

human paring project based on caffe tools

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SegNet_Source

The code of source-only training for our method

JADF-caffe

Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection

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3DTrans

An open-source codebase for exploring the Autonomous Driving-oriented Transfer Learning Techniques

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Conditional_GANs

A tensorflow implementation about conditional generative adversarial nets

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few-shot-meta-baseline

A New Meta-Baseline for Few-Shot Learning

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OpenPCDet

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

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UniDet

Object detection on multiple datasets with an automatically learned unified label space.

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boZhang.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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ChatGPT

đź”® ChatGPT Desktop Application (Mac, Windows and Linux)

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DomainBed

DomainBed is a suite to test domain generalization algorithms

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Fewshot_Detection

Few-shot Object Detection via Feature Reweighting

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gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

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holoclean

A Machine Learning System for Data Enrichment.

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lancedb

Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!

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llama

Inference code for LLaMA models

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llm.c

LLM training in simple, raw C/CUDA

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MetaTransformer

Meta-Transformer for Unified Multimodal Learning

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MiniGPT-4

MiniGPT-4: Enhancing Vision-language Understanding with Advanced Large Language Models

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ONCE_Benchmark

One Million Scenes for Autonomous Driving

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poolformer

PoolFormer: MetaFormer is Actually What You Need for Vision

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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SimChart9K

The proposed simulated dataset consisting of 9,536 charts and associated data annotations in CSV format.

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ST3D

(CVPR 2021) ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

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stable-diffusion

A latent text-to-image diffusion model

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SwinDocSegmenter

An End-to-End Unified Domain Adaptive Transformer for Document Instance Segmentation

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Taylor_pruning

Pruning Neural Networks with Taylor criterion in Pytorch

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Yuan-2.0

Yuan 2.0 Large Language Model

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