mlsanityData to 7 Oct 2026

ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes

arXiv 2106.02740 ↗First posted 4 Jun 2021cs.CVcited by 47

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Abstract (arXiv)

Less than 35% of recyclable waste is being actually recycled in the US, which leads to increased soil and sea pollution and is one of the major concerns of environmental researchers as well as the common public. At the heart of the problem are the inefficiencies of the waste sorting process (separating paper, plastic, metal, glass, etc.) due to the extremely complex and cluttered nature of the waste stream. Recyclable waste detection poses a unique computer vision challenge as it requires detection of highly deformable and often translucent objects in cluttered scenes without the kind of context information usually present in human-centric datasets. This challenging computer vision task currently lacks suitable datasets or methods in the available literature. In this paper, we take a step towards computer-aided waste detection and present the first in-the-wild industrial-grade waste detection and segmentation dataset, ZeroWaste. We believe that ZeroWaste will catalyze research in object detection and semantic segmentation in extreme clutter as well as applications in the recycling domain. Our project page can be found at http://ai.bu.edu/zerowaste/.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). Builds on 33 of its 62 references that are in the map. First posted on arXiv 4 Jun 2021.

Builds on

33 of 62 references.

References · 33

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  5. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  6. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
  7. 2016Pyramid Scene Parsing Networkcited by 2,472
  8. 2015Learning Deep Features for Discriminative Localizationcited by 2,430
  9. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  10. 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,154
  11. 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,483
  12. 2018BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learningcited by 1,282
21 more
  1. 2016COCO-Stuff: Thing and Stuff Classes in Contextcited by 858
  2. 2018RISE: Randomized Input Sampling for Explanation of Black-box Modelscited by 825
  3. 2020Image Segmentation Using Deep Learning: A Surveycited by 659
  4. 2019Segmentation Transformer: Object-Contextual Representations for Semantic Segmentationcited by 573
  5. 2020Semi-Supervised Semantic Segmentation with Cross-Consistency Trainingcited by 375
  6. 2019Panoptic-DeepLabcited by 362
  7. 2018Scale-recurrent Network for Deep Image Deblurringcited by 332
  8. 2018Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentationcited by 321
  9. 2020Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentationcited by 299
  10. 2016Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learningcited by 209
  11. 2016Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentationcited by 198
  12. 2016What makes ImageNet good for transfer learning?cited by 192
  13. 2019Scale-Aware Trident Networks for Object Detectioncited by 159
  14. 2019Semi-Supervised Semantic Segmentation with High- and Low-level Consistencycited by 147
  15. 2020Weakly-Supervised Semantic Segmentation via Sub-category Explorationcited by 145
  16. 2021Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentationcited by 127
  17. 2015Constrained Convolutional Neural Networks for Weakly Supervised Segmentationcited by 100
  18. 2021Bootstrapping Semantic Segmentation with Regional Contrastcited by 80
  19. 2020Structured Consistency Loss for semi-supervised semantic segmentationcited by 39
  20. 2020TACO: Trash Annotations in Context for Litter Detectioncited by 38
  21. 2021Puzzle-CAM: Improved localization via matching partial and full featurescited by 37

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 11; 2025: 14; 2026: 14.

47 papers.

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  1. 2023Segment Anythingcited by 8,158
  2. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  3. 2023CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentationcited by 215
  4. 2025DICEPTION: A Generalist Diffusion Model for Visual Perceptual Taskscited by 37
  5. 2023What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentationcited by 24
  6. 2023Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterpartscited by 18
  7. 2023TRansPose: Large-Scale Multispectral Dataset for Transparent Objectcited by 15
  8. 2024ZIM: Zero-Shot Image Matting for Anythingcited by 15
  9. 2025SAM2 for Image and Video Segmentation: A Comprehensive Surveycited by 13
  10. 2024ASAM: Boosting Segment Anything Model with Adversarial Tuningcited by 12
  11. 2025TranSplat: Surface Embedding-guided 3D Gaussian Splatting for Transparent Object Manipulationcited by 9
  12. 2023VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sortingcited by 6
35 more
  1. 2023Stable Segment Anything Modelcited by 6
  2. 2024SpectralWaste Dataset: Multimodal Data for Waste Sorting Automationcited by 6
  3. 2024High-Quality Mask Tuning Matters for Open-Vocabulary Segmentationcited by 5
  4. 2025Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentationcited by 5
  5. 2026Vision as Unified Multimodal Generationcited by 5
  6. 2025Show or Tell? Effectively prompting Vision-Language Models for semantic segmentationcited by 4
  7. 2024The State of Computer Vision Research in Africacited by 3
  8. 2025Test-Time Optimization for Domain Adaptive Open Vocabulary Segmentationcited by 3
  9. 2024FANet: Feature Amplification Network for Semantic Segmentation in Cluttered Backgroundcited by 2
  10. 2026GlobalWasteData: A Large-Scale, Integrated Dataset for Robust Waste Classification and Environmental Monitoringcited by 2
  11. 2024WasteGAN: Data Augmentation for Robotic Waste Sorting through Generative Adversarial Networkscited by 1
  12. 2024COSNet: A Novel Semantic Segmentation Network using Enhanced Boundaries in Cluttered Scenescited by 1
  13. 2025Temporal-consistent CAMs for Weakly Supervised Video Segmentation in Waste Sortingcited by 1
  14. 2025Show or Tell? A Benchmark To Evaluate Visual and Textual Prompts in Semantic Segmentationcited by 1
  15. 2025Learning Using Privileged Information for Litter Detectioncited by 1
  16. 2025StreetView-Waste: A Multi-Task Dataset for Urban Waste Managementcited by 1
  17. 2026An Ensemble Learning Approach towards Waste Segmentation in Cluttered Environmentcited by 1
  18. 2023Visual Material Characteristics Learning for Circular Healthcarecited by 0
  19. 2024Garbage Segmentation and Attribute Analysis by Robotic Dogscited by 0
  20. 2024"ScatSpotter" -- A Dog Poop Detection Datasetcited by 0
  21. 2025Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sortingcited by 0
  22. 2025Robust and Label-Efficient Deep Waste Detectioncited by 0
  23. 2025Waste-Bench: A Comprehensive Benchmark for Evaluating VLLMs in Cluttered Environmentscited by 0
  24. 2025WS2: Weakly Supervised Segmentation using Before-After Supervision in Waste Sortingcited by 0
  25. 2026SortWaste: A Densely Annotated Dataset for Object Detection in Industrial Waste Sortingcited by 0
  26. 2026SPDA-SAM: A Self-prompted Depth-Aware Segment Anything Model for Instance Segmentationcited by 0
  27. 2026Segment Anything with Robust Uncertainty-Accuracy Correlationcited by 0
  28. 2026PrAda: Few-Shot Visual Adaptation for Text-Prompted Segmentationcited by 0
  29. 2026SteelDS: A High-Resolution Video Dataset of E40 Steel Scrap for Object Detection and Instance Segmentationcited by 0
  30. 2026Parameter-Efficient Fine-Tuning of Large Pretrained Models for Instance Segmentation Taskscited by 0
  31. 2026Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Backgroundcited by 0
  32. 2026Prompting Diffusion Models for Zero-Shot Instance Segmentationcited by 0
  33. 2026Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8ncited by 0
  34. 2026Training-free Suction Grasp Detection for Deformed Aseptic Cartons Using Vision-Language Models and Geometric Surface Scoringcited by 0
  35. 2026Preference-Guided Adaptation for Open-Vocabulary Semantic Segmentation via Prompt Disagreementcited by 0