Ronghang Hu

seg_every_thing. Code release for Hu et al., Learning to Segment Every Thing. in CVPR, 2018.

n2nmn. Code release for Hu et al. Learning to Reason: End-to-End Module Networks for Visual Question Answering. in ICCV, 2017

tensorflow_compact_bilinear_pooling. Compact Bilinear Pooling in TensorFlow

speaker_follower. Code release for Fried et al., Speaker-Follower Models for Vision-and-Language Navigation. in NeurIPS, 2018.

natural-language-object-retrieval. Code release for Hu et al. Natural Language Object Retrieval, in CVPR, 2016

lcgn. Code release for Hu et al., Language-Conditioned Graph Networks for Relational Reasoning. in ICCV, 2019

text_objseg. Code release for Hu et al. Segmentation from Natural Language Expressions. in ECCV, 2016

snmn. Code release for Hu et al., Explainable Neural Computation via Stack Neural Module Networks. in ECCV, 2018

cmn. Code release for Hu et al. Modeling Relationships in Referential Expressions with Compositional Modular Networks. in CVPR, 2017

mmf. A modular framework for Visual Question Answering research by the FAIR A-STAR team

vit_10b_fsdp_example. See details in https://github.com/pytorch/xla/blob/r1.12/torch_xla/distributed/fsdp/README.md

gqa_single_hop_baseline. A simple but well-performing "single-hop" visual attention model for the GQA dataset

moco_v3_tpu. Python

vqa-maskrcnn-benchmark-m4c. Used in M4C feature extraction script: https://github.com/facebookresearch/mmf/blob/project/m4c/projects/M4C/scripts/extract_ocr_frcn_feature.py

caffe. Caffe: a fast open framework for deep learning.

cc_torch. Jupyter Notebook

SanguoshaEX. Sanguosha EX: An Open Source PC Game Based on Popular Desktop Game "Sanguosha"

tech-interview-handbook. 💯 Algorithms study materials, behavioral content and tips for rocking your coding interview

visualnet_label. An Online Tool for Rigid Object Landmark Labeling

detectron2_vitdet. Python

awesome-python. A curated list of awesome Python frameworks, libraries, software and resources

torch_generic_nms. Cuda

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.

attention-is-all-you-need-pytorch. A PyTorch implementation of the Transformer model in "Attention is All You Need".

xla. Enabling PyTorch on Google TPU

mae. PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

vilbert_beta. Jupyter Notebook

visualbert. Code for the paper "VisualBERT: A Simple and Performant Baseline for Vision and Language"

ptxla_scaling_examples. A list of examples for model scaling in PyTorch/XLA

vqa.pytorch. Visual Question Answering in Pytorch

VideoMAE. [NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

mhex_graph. Modified Hierarchy-Exclusion Graph (MHEX Graph)

Algorithm_Interview_Notes-Chinese. 2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

tpu_profiling. Profiling analyses and comparisons between PyTorch/XLA and JAX

text_objseg_caffe. Caffe implementation for Hu et al. Segmentation for Natural Language Expressions in arXiv:1603.06180, 2016 http://ronghanghu.com/text_objseg

fast-rcnn. Fast R-CNN

Semantic-SAM. Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"

sam2. The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

TrackEval. HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).

lxmert. PyTorch code of our EMNLP 2019 paper "LXMERT"