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[CVPR 2025] Official repository of the paper "Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation"
A curated publication list on open vocabulary semantic segmentation and related area (e.g. zero-shot semantic segmentation) resources..
[AAAI'25] Official Code for “Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community"
The Paper List of Large Multi-Modality Model (Perception, Generation, Unification), Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Ins…
EVE Series: Encoder-Free Vision-Language Models from BAAI
[CVPR2025W] Official repository for the paper: "Show or Tell? A Benchmark To Evaluate Visual and Textual Prompts in Semantic Segmentation"
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Codes and dataset (iSAID-5i) for Scale-aware Detailed Matching for Few-Shot Aerial Image Semantic Segmentation
[IGARSS 2024] Code for "CLIP-Guided Source-Free Object Detection in Aerial Images"
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image …
Official PyTorch implementation of ODISE: Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models [CVPR 2023 Highlight]
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
Combining Segment Anything (SAM) with Grounded DINO for zero-shot object detection and CLIPSeg for zero-shot segmentation
[AAAI2021] The code of “Similarity Reasoning and Filtration for Image-Text Matching”
Experiment on combining CLIP with SAM to do open-vocabulary image segmentation.
Windows 11 Classic Right-Click Menu Editor
TED parallel Corpora is growing collection of Bilingual parallel corpora, Multilingual parallel corpora and Monolingual corpora extracted from TED talks www.ted.com for 109 world languages.