[CVPR2023] Official Implementation of "DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets"
-
Updated
Jul 2, 2024 - Python
Backbone.js supplies structure to JavaScript-heavy applications by providing models with key-value binding and custom events, collections with a rich API of enumerable functions, views with declarative event handling, and connects it all to your existing application over a RESTful JSON interface. Backbone.js was originally extracted from the Rails application DocumentCloud. Philosophically, Backbone is an attempt to discover the minimal set of data-structuring (models and collections) and user interface (views and URLs) primitives that are generally useful when building web applications with JavaScript. Backbone is a library, not a framework. Synchronous events are used as the fundamental building block over constantly polling data. The main pars of Backbone are:
[CVPR2023] Official Implementation of "DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets"
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"
[CVPR 2023 Highlight] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
[ICLR 2024] Official PyTorch implementation of FasterViT: Fast Vision Transformers with Hierarchical Attention
More readable and flexible yolov5 with more backbone(gcn, resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer, etc) and (cbam,dcn and so on), and tensorrt
The official repo for [TPAMI'23] "Vision Transformer with Quadrangle Attention"
🔥🔥🔥 专注于YOLOv5,YOLOv7、YOLOv8、YOLOv9改进模型,Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
⭐⭐⭐ Pytorch implementation of Attentiom, Backbone, ViT, MLP, Re-parameter, Convolution, very flexible module combination.
This is a warehouse for FasterNet-Pytorch-model, can be used to train your image-datasets for classification tasks.
[ICML 2023] Official PyTorch implementation of Global Context Vision Transformers
a pytorch implementation of some models, include many attention mechanism, convolution layer and backbone etc.
This repository contains the main methods for the wash trading analysis on the nft's market.
[TPAMI 2023] This is an official implementation for "Vicinity Vision Transformer".
A testbed for backbones in DG. Repository for "Back-to-Bones: Rediscovering the Role of Backbones in Domain Generalization" (Angarano et al., 2022).
detectron2 backbone: resnet18, efficientnet, hrnet, mobilenet v2, resnest, bifpn
Official PyTorch implementation of Fully Attentional Networks
The official repo for [ECCV'22] "VSA: Learning Varied-Size Window Attention in Vision Transformers"
Prevention of accidents in school zones using deep learning
Created by Jeremy Ashkenas
Released October 13, 2010