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Awesome-Referring-Image-Segmentation
:books: A collection of papers about Referring Image Segmentation.
https://github.com/MarkMoHR/Awesome-Referring-Image-Segmentation
- MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
- GRES: Generalized Referring Expression Segmentation
- ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
- ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
- PhraseCut: Language-based Image Segmentation in the Wild
- CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions - ref+) |
- Modeling context in referring expressions
- Modeling context in referring expressions
- Generation and comprehension of unambiguous object descriptions
- Referit game: Referring to objects in photographs of natural scenes
- 1st MeViS Challenge - level Video Understanding in the Wild](https://www.vspwdataset.com/Workshop2024.html) | May 2024| [[CodaLab]](https://codalab.lisn.upsaclay.fr/competitions/15094) |
- CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation
- Curriculum Point Prompting for Weakly-Supervised Referring Image Segmentation
- GSVA: Generalized Segmentation via Multimodal Large Language Models
- Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation
- Unveiling Parts Beyond Objects: Towards Finer-Granularity Referring Expression Segmentation - Xuan/MRES) [[webpage]](https://rubics-xuan.github.io/MRES/) |
- Mask Grounding for Referring Image Segmentation - grounding/) |
- Towards Robust Referring Image Segmentation - ref-seg) |
- LISA: Reasoning Segmentation via Large Language Model - research/LISA) |
- Referring Image Segmentation via Joint Mask Contextual Embedding Learning and Progressive Alignment Network - segmentation) |
- Unsupervised Domain Adaptation for Referring Semantic Segmentation
- CARIS: Context-Aware Referring Image Segmentation
- Text Augmented Spatial-aware Zero-shot Referring Image Segmentation
- Bilateral Knowledge Interaction Network for Referring Image Segmentation
- Advancing Referring Expression Segmentation Beyond Single Image - res) |
- Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency
- Shatter and Gather: Learning Referring Image Segmentation with Text Supervision
- Referring Image Segmentation Using Text Supervision
- Beyond One-to-One: Rethinking the Referring Image Segmentation - DMMI) |
- Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation
- Segment Everything Everywhere All at Once - Decoder/Segment-Everything-Everywhere-All-At-Once) |
- SLViT: Scale-Wise Language-Guided Vision Transformer for Referring Image Segmentation
- WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation
- Multi-Modal Mutual Attention and Iterative Interaction for Referring Image Segmentation
- X-Decoder: Generalized Decoding for Pixel, Image and Language - Decoder) [[project]](https://x-decoder-vl.github.io/) |
- Learning to Segment Every Referring Object Point by Point - RES) |
- Meta Compositional Referring Expression Segmentation
- Zero-shot Referring Image Segmentation with Global-Local Context Features - Yu/Zero-shot-RIS) |
- PolyFormer: Referring Image Segmentation as Sequential Polygon Generation - science/polygon-transformer) [[project]](https://polyformer.github.io/) |
- GRES: Generalized Referring Expression Segmentation
- Contrastive Grouping with Transformer for Referring Image Segmentation
- Semantics-Aware Dynamic Localization and Refinement for Referring Image Segmentation
- Towards Robust Referring Image Segmentation - ref-seg) [[project]](https://lxtgh.github.io/project/robust_ref_seg/) |
- Learning From Box Annotations for Referring Image Segmentation - Supervised-RIS) |
- Instance-Specific Feature Propagation for Referring Segmentation
- LAVT: Language-Aware Vision Transformer for Referring Image Segmentation - RIS) |
- CRIS: CLIP-Driven Referring Image Segmentation
- ReSTR: Convolution-free Referring Image Segmentation Using Transformers
- Two-stage Visual Cues Enhancement Network for Referring Image Segmentation - net) |
- Vision-Language Transformer and Query Generation for Referring Segmentation - Language-Transformer) |
- MDETR - Modulated Detection for End-to-End Multi-Modal Understanding
- Encoder Fusion Network with Co-Attention Embedding for Referring Image Segmentation
- Bottom-Up Shift and Reasoning for Referring Image Segmentation
- Locate then Segment: A Strong Pipeline for Referring Image Segmentation
- Cascade Grouped Attention Network for Referring Expression Segmentation
- Linguistic Structure Guided Context Modeling for Referring Image Segmentation - Refseg) |
- Referring Image Segmentation via Cross-Modal Progressive Comprehension - Refseg) |
- Bi-directional Relationship Inferring Network for Referring Image Segmentation - BRINet) |
- PhraseCut: Language-based Image Segmentation in the Wild
- Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation
- Dual Convolutional LSTM Network for Referring Image Segmentation
- See-Through-Text Grouping for Referring Image Segmentation
- Referring Expression Object Segmentation with Caption-Aware Consistency
- Cross-Modal Self-Attention Network for Referring Image Segmentation - Net) |
- Key-Word-Aware Network for Referring Expression Image Segmentation - word-aware-network-pycaffe) |
- Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries - Uniandes/DMS) |
- Referring Image Segmentation via Recurrent Refinement Networks
- MAttNet: Modular Attention Network for Referring Expression Comprehension
- Recurrent Multimodal Interaction for Referring Image Segmentation - phrasecut-public) |
- Segmentation from natural language expressions
- PhraseClick: Toward Achieving Flexible Interactive Segmentation by Phrase and Click
- Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation
- LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation
- SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
- Local-Global Context Aware Transformer for Language-Guided Video Segmentation
- Temporal Collection and Distribution for Referring Video Object Segmentation
- HTML: Hybrid Temporal-scale Multimodal Learning Framework for Referring Video Object Segmentation
- MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
- OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation
- Spectrum-guided Multi-granularity Referring Video Object Segmentation - miao/SgMg) |
- Towards Robust Referring Video Object Segmentation with Cyclic Relational Consistency
- Multi-Attention Network for Compressed Video Referring Object Segmentation
- End-to-End Referring Video Object Segmentation with Multimodal Transformers
- Language as Queries for Referring Video Object Segmentation
- Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation
- Multi-Level Representation Learning with Semantic Alignment for Referring Video Object Segmentation
- You Only Infer Once: Cross-Modal Meta-Transfer for Referring Video Object Segmentation
- Rethinking Cross-modal Interaction from a Top-down Perspective for Referring Video Object Segmentation
- ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation
- RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation
- URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark - Youtube-VOS) |
- Video Object Segmentation with Language Referring Expressions
- Text-Guided Graph Neural Networks for Referring 3D Instance Segmentation
- InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring