x-clip VS CapDec

Compare x-clip vs CapDec and see what are their differences.

x-clip

A concise but complete implementation of CLIP with various experimental improvements from recent papers (by lucidrains)

CapDec

CapDec: SOTA Zero Shot Image Captioning Using CLIP and GPT2, EMNLP 2022 (findings) (by DavidHuji)
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x-clip CapDec
1 3
651 174
- -
5.8 5.6
7 months ago 4 months ago
Python Python
MIT License MIT License
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x-clip

Posts with mentions or reviews of x-clip. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-19.
  • [D] Problems with proprietary datasets
    4 projects | /r/MachineLearning | 19 May 2022
    Now is it possible that some of these images were a part of train set of these models ? Maybe, but we can't really be sure without having access to the original dataset. To this end, are there any works that study this phenomenon more deeply and technically (with metrics etc.) ? I know few attempts to reproduce DALL-E and CLIP on open datasets but not sure whether such studies have been performed. Unfortunately I lack both the resources as well as technical competency to perform such studies myself but would love to see if you folks know anything about this.

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 x-clip and CapDec you can also consider the following projects:

DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

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

CoCa-pytorch - Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

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

VehicleFinder-CTIM

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

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"

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

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

GroupViT - Official PyTorch implementation of GroupViT: Semantic Segmentation Emerges from Text Supervision, CVPR 2022.