January 5, 2022 Semantic

Zero-Shot Semantic Segmentation

@article{xu2021ss, title={End-to-End Semi-Supervised Object Detection with Soft Teacher}, author={Xu, Mengde and Zhang, Zheng and Hu, Han and Wang, Jianfeng and Wang, Lijuan and Wei, Fangyun and Bai, Xiang and Liu, Zicheng}, journal={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, year={2021} }

December 6, 2021 Semantic

A joke conlang with minimal semantics

Reserved Defined Words Word Function fo Terminates an adjective block tu Converts an adjective block or sentence to a noun to Terminates ‘tu’ Word Classes for Undefined Words Word Class Description Noun A thing Verb An action, state, or occurrence Adjective A descriptor of a noun or verb Modifier A word modifying an adjective Converter Converts a noun to an adjective that conveys a relationship to the noun List of Syntactic Constructions Adjective Phrase An adjective phrase conveys a single […]

October 19, 2021 Semantic

ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration

News & Updates (24/08/2021) Release the demo to perform fine-grained semantic alignments using the pretrained ROSITA model. (15/08/2021) Release the basic framework for ROSITA, including the pretrained base ROSITA model, as well as the scripts to run the fine-tuning and evaluation on three downstream tasks (i.e., VQA, REC, ITR) over six datasets. Introduction This repository contains source code necessary to reproduce the results presented in our ACM MM paper ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration, […]

October 13, 2021 Semantic

Learning to Regress Bodies from Images using Differentiable Semantic Rendering

Getting Started DSR has been implemented and tested on Ubuntu 18.04 withpython 3.6. Clone the repo: git clone https://github.com/saidwivedi/DSR.git Install the requirements using conda: # conda source install_conda.sh Preparation of Data For evaluation, you need to download the pretrained DSR model and SMPL body models. Run the command following command For both evaluation and training, we use data processing techinque similar to SPIN. Kindly refer to their repo for more details.

September 26, 2021 Semantic

An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc

This is the official implementation of our BEV-Seg3D-Net, an efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc. Features of our framework/model: leveraging various proven methods in 2D segmentation for 3D tasks achieve competitive performance in the SensatUrban benchmark fast inference process, about 1km^2 area per minute with RTX 3090. To be done: add more complex/efficient fusion models add more backbone like ResNeXt, HRNet, DenseNet, etc. add more novel projection methods like pointpillars For technical details, […]