referring-expression-segmentation

[CVPR'23] Universal Instance Perception as Object Discovery and Retrieval

[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale

[CVPR 2023 Highlight & IJCV 2026] GRES: Generalized Referring Expression Segmentation

[ICCV 2023 & TPAMI 2025] MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions

A benchmark dataset for GREx: GRES, GREC, and GREG [CVPR 2023 & IJCV 2026]

Code release for "UniVS: Unified and Universal Video Segmentation with Prompts as Queries" (CVPR2024)

[CVPR2020] Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation, CVPR2020 (oral)

[CVPR 2025] Official PyTorch Implementation of GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation

A lightweight codebase for referring expression comprehension and segmentation

Official PyTorch implementation of “MaskRIS: Semantic Distortion-aware Data Augmentation for Referring Image Segmentation”

[NeurIPS 2025] "SaFiRe: Saccade-Fixation Reiteration with Mamba for Referring Image Segmentation" https://arxiv.org/pdf/2510.10160

[NeurIPS 2025] "SaFiRe: Saccade-Fixation Reiteration with Mamba for Referring Image Segmentation" https://arxiv.org/pdf/2510.10160

[MULA Workshop @ CVPR 2022] Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters

VIPA: Visual Informative Part Attention Framework for Transformer-based Referring Image Segmentation

🌟 Build a PyTorch implementation of Google's PaliGemma model for advanced vision-language tasks, including object detection and segmentation.

PyTorch implementation of Google's PaliGemma vision-language model with VQ-VAE decoder for processing referring expression segmentation outputs. Supports detection, segmentation, VQA, and captioning.