DeepViewAgg VS CapDec

Compare DeepViewAgg vs CapDec and see what are their differences.

DeepViewAgg

[CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation" (by drprojects)

CapDec

CapDec: SOTA Zero Shot Image Captioning Using CLIP and GPT2, EMNLP 2022 (findings) (by DavidHuji)
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DeepViewAgg CapDec
4 3
215 170
- -
4.8 5.6
9 months ago 4 months ago
Python Python
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DeepViewAgg

Posts with mentions or reviews of DeepViewAgg. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-11.

CapDec

Posts with mentions or reviews of CapDec. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-08.

What are some alternatives?

When comparing DeepViewAgg and CapDec you can also consider the following projects:

torch-points3d - Pytorch framework for doing deep learning on point clouds.

mmf - A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

MonoScene - [CVPR 2022] "MonoScene: Monocular 3D Semantic Scene Completion": 3D Semantic Occupancy Prediction from a single image

pytorch-widedeep - A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

3DCoMPaT-v2 - 3DCoMPaT++: An improved large-scale 3D vision dataset for compositional recognition

img2dataset - Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.

MAGIC - Language Models Can See: Plugging Visual Controls in Text Generation

LAVIS - LAVIS - A One-stop Library for Language-Vision Intelligence

x-clip - A concise but complete implementation of CLIP with various experimental improvements from recent papers