This repo contains fixes for MaskTrackRCNN paper to make it compatible on PyTorch 1.6+.
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Updated
Aug 23, 2023 - Python
This repo contains fixes for MaskTrackRCNN paper to make it compatible on PyTorch 1.6+.
Code release for "BoxVIS: Video Instance Segmentation with Box Annotation"
Learning Better Video Query with SAM for Video Instance Segmentation (TCSVT 2024)
Dynamic MNIST digit sequences for video instance segmentation with optical flow data.
CenterMask is powered with MaskTrackRCNN tracking algorithm for video instance segmentation.
Open-vocabulary Video Instance Segmentation Codebase built upon Detectron2, which is really easy to use.
Code release for "MDQE: Mining Discriminative Query Embeddings to Segment Occluded Instances on Challenging Videos"(CVPR2023)
Implementation of joint construction of Mask/BBox heads in QDTrack-mots for joint training research
A video instance segmentation codebase based on OpenMMLab projects.
This repository captures our work on Video Instance Segmentation, as a part of our CS 534 AI course project, under Prof. Jacob Whitehill. We describe and analyze the experimental trials performed on the baseline ([CVPRW 2021] - Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation).
The repository for TLTM: Two-Level Temporal Relation Model for Online Video Instance Segmentation.
[CVPR 2021] Youtube-VIS 2021 3rd place, [CVPR 2020] winner DAVIS 2020. Code for mask selection based methods.
DeVIS: Making Deformable Transformers Work for Video Instance Segmentation
UNOFFICIAL implement of MaskTrackRCNN for video instance segmentation via mmdetection 2.11.0.
DVIS: Decoupled Video Instance Segmentation Framework
Code release for "STMask: Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentation"(CVPR2021)
Code release for "UniVS: Unified and Universal Video Segmentation with Prompts as Queries" (CVPR2024)
[CVPRW 2021] - Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation
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