Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal".
Patch-wise Adversarial Removal (PAR) is a new decision-based black-box attack against vision transformers, which divides images into patches through a coarse-to-fine search process and compresses the noise on each patch separately.
Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters" Pipeline of CLIP-Adapter CLIP-Adapter is a drop-in modul
Direct Molecular Conformation Generation This repository contains the code for Direct Molecular Conformation Generation (DMCG). Dataset Download rdkit
Python Streaming Anomaly Detection (PySAD) PySAD is an open-source python framework for anomaly detection on streaming multivariate data. Documentatio
The Joy of Neural Painting Learning Neural Painters Fast! using PyTorch and Fast.ai Blogpost with more details: The Joy of Neural Painting The impleme
MatConvNet implementation of the FCN models for semantic segmentation This package contains an implementation of the FCN models (training and evaluati
TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr
Intro This repository contains code to generate data and reproduce experiments from our NeurIPS 2019 paper: Boris Knyazev, Graham W. Taylor, Mohamed R
InstanceRefer InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring
fasterGICP This package is an improvement of fast_gicp Please cite our paper if possible. W. Jikai, M. Xu, F. Farzin, D. Dai and Z. Chen, "FasterGICP:
STMTrack This is the official implementation of the paper: STMTrack: Template-free Visual Tracking with Space-time Memory Networks. Setup Prepare Anac
Knowledge Distillation for BERT Unsupervised Domain Adaptation Official PyTorch implementation | Paper Abstract A pre-trained language model, BERT, ha
RuleBERT: Teaching Soft Rules to Pre-Trained Language Models (Paper) (Slides) (Video) RuleBERT is a pre-trained language model that has been fine-tune
GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear
USDAN The implementation of Unified unsupervised and semi-supervised domain adaptation network for cross-scenario face anti-spoofing, which is accepte
LongScientificFormer For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training. Some code
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation CVPR2021(oral) [arxiv] Requirements python3.7 pytorch==
ML2 Takehome Project Reimplementing the paper: Cascaded Pyramid Network for Multi-Person Pose Estimation Dataset The model uses the COCO dataset which
RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p
Grounding Representation Similarity with Statistical Testing This repo contains code to replicate the results in our paper, which evaluates representa
READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz
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