PyTorch Image Classification Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to

Predicting-Student-Attentiveness-using-OpenCV The model will predict if a student is attentive or not through facial parameter received through the st

MVSS-Net Code and models for ICCV 2021 paper: Image Manipulation Detection by Multi-View Multi-Scale Supervision Update 22.02.17, Pretrained model for

BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition

GSL - Zero-shot Synthesis with Group-Supervised Learning Figure: Zero-shot synthesis performance of our method with different dataset (iLab-20M, RaFD,

Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation This is the code relat

SPARSEDNN **If you want to use this repo, please send me an email: [email pro

Generative Occupancy Fields for 3D Surface-Aware Image Synthesis (NeurIPS 2021) Project Page | Paper Xudong Xu, Xingang Pan, Dahua Lin and Bo Dai GOF

snn-localization repo PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch. Install Dependencies Orig

Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks VinVL: Revisiting Visual Representations in Vision-Language Models Updates

SLIP: Self-supervision meets Language-Image Pre-training What you can find in this repo: Pre-trained models (with ViT-Small, Base, Large) and code to

NeuroFind A solution to the to the Task given by the Oberseminar of Messtechnik

SAS: Self-Augmentation Strategy for Language Model Pre-training This repository

Group-Free 3D Object Detection via Transformers By Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong. This repo is the official implementation of "Group-

CoReNet CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image. It produces coherent reconstructions, where all objec

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli

Streamlit Demo: Deep Dream A Streamlit demo demonstrating the Deep Dream technique. Adapted from the TensorFlow Deep Dream tutorial How to run this de

ssnt-loss ℹ️ This is a WIP project. the implementation is still being tested. A pure PyTorch implementation of the loss described in "Online Segment t

News 05/10/2022 To make the comparison on ScanNet easier, we provide all quantitative and qualitative results of baselines here, including COLMAP, COL