Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? | Paper Citation Record

Observation 63c6daad-ac3b-4630-82c9-10770c5c8c94 · outbound

This paper cites On the unreasonable vulnerability of transformers for image restoration-and an easy fix.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? On the unreasonable vulnerability of transformers for image restoration-and an easy fix

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.532058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5bd469ff-9a9e-434e-83a7-e967cfbab304 · outbound

This paper cites Improving stability during upsampling – on the importance of spatial context, 2023.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Improving stability during upsampling – on the importance of spatial context, 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.506225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dbf62097-ec3e-40e1-9bdb-d35f46656372 · outbound

This paper cites Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.297025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7585aff1-8e91-4b52-bae5-2dc8735742b6 · outbound

This paper cites CosPGD: an efficient white-box adversarial attack for pixel- wise prediction tasks.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? CosPGD: an efficient white-box adversarial attack for pixel- wise prediction tasks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.490725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca77a7ae-e969-4dca-a6f2-83e5af3863f6 · outbound

This paper cites Roll the dice: Monte carlo downsampling as a low-cost adversarial defence, 2024.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Roll the dice: Monte carlo downsampling as a low-cost adversarial defence, 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.474589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dde43072-9a83-481f-b290-ebd84e4ce665 · outbound

This paper cites DispBench.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? DispBench

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.459009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 79167dfa-f2ac-43d7-8280-a1849b6fec39 · outbound

This paper cites FlowBench: A Robustness Benchmark for Optical Flow Estimation, 2025.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? FlowBench: A Robustness Benchmark for Optical Flow Estimation, 2025

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.442510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eaf1befe-a346-44ff-bfed-c009ca8b15d1 · outbound

This paper cites On the robustness of semantic segmentation models to adversarial attacks.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? On the robustness of semantic segmentation models to adversarial attacks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.426919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 10732ae6-fdf6-4c1c-8580-a716273d7d7f · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? BEiT: BERT Pre-Training of Image Transformers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.325677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef0db748-3ccb-4e97-becf-877d10c0b236 · outbound

This paper cites Segmentmeifyoucan: A benchmark for anomaly segmentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Segmentmeifyoucan: A benchmark for anomaly segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.411252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c4456bef-cf0e-4f4b-85c7-ac6df8ad7fc9 · outbound

This paper cites Rethinking atrous convolution for semantic image segmentation, 2017.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Rethinking atrous convolution for semantic image segmentation, 2017

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.396065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 83d7519c-31dc-4298-bc23-0c8c63973b50 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.380772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 54698f5d-72ce-4603-937f-c3cc8184ee10 · outbound

This paper cites Schwing, Alexan- der Kirillov, and Rohit Girdhar.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Schwing, Alexan- der Kirillov, and Rohit Girdhar

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.344677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29fa68fe-43fb-4dc4-af46-255ec15e0b45 · outbound

This paper cites Xception: Deep learning with depthwise separable convolutions.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Xception: Deep learning with depthwise separable convolutions

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.356909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 30f9e841-1c25-4a4b-be9e-874fefe99a23 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? The cityscapes dataset for semantic urban scene understanding

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.341130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a00a055-2b15-4a36-afe0-e4bf089d892c · outbound

This paper cites RobustBench: a standardized adversarial robustness benchmark.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? RobustBench: a standardized adversarial robustness benchmark

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.326200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e42e1b0-4126-4ce8-a106-1deed21695da · outbound

This paper cites 2 net for generalized zero-label semantic seg- mentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? 2 net for generalized zero-label semantic seg- mentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.311361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2e67bd17-865a-4fac-816a-f9886cbfcbd9 · outbound

This paper cites Weakly-supervised domain adaptive semantic segmentation with prototypical contrastive learning.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Weakly-supervised domain adaptive semantic segmentation with prototypical contrastive learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.367069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 400bd64c-476d-4910-9287-971f9afa6682 · outbound

This paper cites Using duck-net for polyp image segmentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Using duck-net for polyp image segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.286049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d9cdc41c-9740-4ede-869a-dfc7e70d37c5 · outbound

This paper cites Everingham, L.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Everingham, L

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.375710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfded571-1905-4c43-94e0-51743f718538 · outbound

This paper cites Everingham, L.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Everingham, L

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.380105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abce55f6-9fc1-4b10-a67b-de2f2927ffa9 · outbound

This paper cites How Do Training Methods Influence the Utilization of Vision Models?.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? How Do Training Methods Influence the Utilization of Vision Models?

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.384599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c18931f6-460f-43e2-a25d-3c302010e1c5 · outbound

This paper cites Robust models are less over-confident.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Robust models are less over-confident

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.389636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6f39f27-275d-4862-8bd9-41c7d2cfcf62 · outbound

This paper cites Frequencylowcut pooling-plug and play against catas- trophic overfitting.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Frequencylowcut pooling-plug and play against catas- trophic overfitting

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.393972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c88656bd-0361-47ed-88ad-c594dfa827bc · outbound

This paper cites Alias- ing and adversarial robust generalization of cnns.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Alias- ing and adversarial robust generalization of cnns

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.233198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 694c9465-05f1-45a1-9831-710e093ea8e8 · outbound

This paper cites Segpgd: An effective and efficient adversarial attack for evaluating and boosting segmentation robustness.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Segpgd: An effective and efficient adversarial attack for evaluating and boosting segmentation robustness

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.219027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 763a6fdd-ba8a-4af3-b9cc-cd541bdd21ad · outbound

This paper cites Robustifying token attention for vision transformers.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Robustifying token attention for vision transformers

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.203910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation acf5b255-f138-417c-85c8-b68206eb9e90 · outbound

This paper cites Semantic contours from inverse detectors.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Semantic contours from inverse detectors

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.189356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2bbd6725-fc38-4809-beb2-9237b9a1ec34 · outbound

This paper cites Hypercolumns for object segmentation and fine-grained localization.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Hypercolumns for object segmentation and fine-grained localization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.174222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f9513829-1b24-413c-82b4-ddda230d25e7 · outbound

This paper cites Deep residual learning for image recognition.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Deep residual learning for image recognition

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.158887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0d660dcb-c70c-4e22-a24c-6cea03c0e006 · outbound

This paper cites Benchmarking neu- ral network robustness to common corruptions and perturba- tions.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Benchmarking neu- ral network robustness to common corruptions and perturba- tions

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.142662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3055bb6c-942f-4d78-9e75-fc6b3920c9af · outbound

This paper cites Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.127344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a39a3a1c-fbd4-4370-8ca6-1e14d24cbf0f · outbound

This paper cites Towards improving robustness of compressed cnns.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Towards improving robustness of compressed cnns

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.111963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bc77b50e-61a4-44b1-bd20-56c8938bf068 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.439330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6e318ba-2493-42a8-842b-2eca3eb3c298 · outbound

This paper cites Benchmarking the robustness of semantic segmentation models.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Benchmarking the robustness of semantic segmentation models

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.097136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e74ca13-d879-4da8-8f6a-1ffe3d872087 · outbound

This paper cites 3d common corruptions and data augmentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? 3d common corruptions and data augmentation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.081917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dab15f4c-0f37-49b9-94af-98a745275f76 · outbound

This paper cites Hierarchical markov random fields for mast cell segmentation in electron microscopic record- ings.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Hierarchical markov random fields for mast cell segmentation in electron microscopic record- ings

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.453422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2763c96d-4db2-4a4b-a053-5abc6cf91f59 · outbound

This paper cites Intra-source style augmentation for improved domain gener- alization.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Intra-source style augmentation for improved domain gener- alization

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.457732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8978df19-28c6-40c4-9bc8-944550820664 · outbound

This paper cites Adversarial supervision makes layout-to-image diffusion models thrive.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Adversarial supervision makes layout-to-image diffusion models thrive

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.048106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b04f1383-2c4b-47e7-8480-769df8f922e3 · outbound

This paper cites Intra-& extra-source exemplar-based style synthesis for im- proved domain generalization.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Intra-& extra-source exemplar-based style synthesis for im- proved domain generalization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.032819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9db4d82f-4a20-4ab5-863a-b5144d699758 · outbound

This paper cites Microsoft coco: Common objects in context.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Microsoft coco: Common objects in context

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.471413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea2b8cf2-4ea8-4e7d-b46d-0381198a2ce9 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Swin transformer: Hierarchical vision transformer using shifted windows

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:29.007498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0de62280-be76-4f30-987c-bc82ee1cd3b1 · outbound

This paper cites Towards Class-wise Robustness Analysis.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Towards Class-wise Robustness Analysis

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.479948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1548466c-6940-4c09-91e3-7229406e9524 · outbound

This paper cites Fair-tat: Improving model fairness using targeted adversarial train- ing.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Fair-tat: Improving model fairness using targeted adversarial train- ing

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.991865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 048e62d2-d26a-480f-a489-1c7dec526ac8 · outbound

This paper cites Object scene flow for au- tonomous vehicles.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Object scene flow for au- tonomous vehicles

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.977595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9b98f928-1aca-4ce7-b16b-0ca999eff05f · outbound

This paper cites Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.493468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9837538e-51f0-43fd-b9cc-59e4fb17f09d · outbound

This paper cites Clas- sification robustness to common optical aberrations.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Clas- sification robustness to common optical aberrations

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.963283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ecebc595-3407-47e6-94a7-901d44cf22db · outbound

This paper cites DCBM: Data-Efficient Visual Concept Bottleneck Models.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? DCBM: Data-Efficient Visual Concept Bottleneck Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.502441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77c12f2a-b619-4706-9ff9-411fc535062f · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? U-net: Convolutional networks for biomedical image segmentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.948192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e4d61a5-d1c2-4290-82b8-d1608a5db297 · outbound

This paper cites ACDC: The adverse conditions dataset with correspondences for se- mantic driving scene understanding.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? ACDC: The adverse conditions dataset with correspondences for se- mantic driving scene understanding

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.933715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ef8e5949-6fe5-47de-b320-0c989218bf41 · outbound

This paper cites Detection defenses: An empty promise against adver- sarial patch attacks on optical flow.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Detection defenses: An empty promise against adver- sarial patch attacks on optical flow

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.515907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 601c5795-5fd0-423e-aaa8-9dec1d7d3b70 · outbound

This paper cites At- tacking motion estimation with adversarial snow.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? At- tacking motion estimation with adversarial snow

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.909288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 88b993d1-a12d-4985-a761-8fdc01b862c1 · outbound

This paper cites A perturbation-constrained adversarial attack for evaluating the 6 robustness of optical flow.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? A perturbation-constrained adversarial attack for evaluating the 6 robustness of optical flow

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.894933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35dd1470-a2be-4724-b353-a6f9ed81a4a7 · outbound

This paper cites Implicit representations for constrained image segmentation.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Implicit representations for constrained image segmentation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.880571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 95a083ae-cf62-4a78-bf3e-06d00d0e5cd9 · outbound

This paper cites Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T23:24:28.534676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81e2a228-35b6-4c98-8d69-2440b64bcdfc · outbound

This paper cites Task driven sensor layouts-joint optimiza- tion of pixel layout and network parameters.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Task driven sensor layouts-joint optimiza- tion of pixel layout and network parameters

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.865834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ce8d4da4-2105-46b1-9de4-649c6ab904f6 · outbound

This paper cites Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.850528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 23c10b78-a594-4674-b802-2e931b40e171 · outbound

This paper cites Unified perceptual parsing for scene understand- ing.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Unified perceptual parsing for scene understand- ing

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.834940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28efdde0-6a60-43db-a7d9-63fec825b981 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Segformer: Simple and efficient design for semantic segmentation with transform- ers

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.819659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d1e727c-3412-4eb9-a8bd-609c18573a7e · outbound

This paper cites Improving 2d feature representations by 3d-aware fine-tuning.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Improving 2d feature representations by 3d-aware fine-tuning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.802499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f212cd9-d2f4-404a-9d89-73d2ccd04b95 · outbound

This paper cites an unresolved cited work.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:24:28.786500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57d58b98-1eb2-4bb3-8101-a7c05b564a84 · outbound

This paper cites Pyramid scene parsing network.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Pyramid scene parsing network

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.770452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9383a667-9ed7-4714-a7b3-2d86eb876930 · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Semantic under- standing of scenes through the ade20k dataset

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:24:28.754623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 44e862bd-bf9f-401e-ac8c-be0726452cb9 · outbound

This paper cites an unresolved cited work.

Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:24:28.738342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers