default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDEvan Shelhamer
Person information
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c20]Saiyue Lyu, Shadab Shaikh, Frederick Shpilevskiy, Evan Shelhamer, Mathias Lécuyer:
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences. NeurIPS 2024- [i25]Saiyue Lyu, Shadab Shaikh, Frederick Shpilevskiy, Evan Shelhamer, Mathias Lécuyer:
Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples. CoRR abs/2406.10427 (2024) - 2023
- [j2]Zhuang Liu
, Hung-Ju Wang, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Evan Shelhamer, Trevor Darrell:
Exploring Simple and Transferable Recognition-Aware Image Processing. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3032-3046 (2023) - [c19]Jin Gao, Jialing Zhang, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang:
Back to the Source: Diffusion-Driven Adaptation to Test-Time Corruption. CVPR 2023: 11786-11796 - [c18]Francesco Croce, Sylvestre-Alvise Rebuffi, Evan Shelhamer, Sven Gowal:
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts. CVPR 2023: 12313-12323 - [i24]Francesco Croce, Sylvestre-Alvise Rebuffi, Evan Shelhamer, Sven Gowal:
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts. CoRR abs/2302.10164 (2023) - 2022
- [c17]Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic:
Object Discovery and Representation Networks. ECCV (27) 2022: 123-143 - [c16]Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, Trevor Darrell, Evan Shelhamer:
Anytime Dense Prediction with Confidence Adaptivity. ICLR 2022 - [c15]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR 2022 - [c14]Francesco Croce, Sven Gowal, Thomas Brunner, Evan Shelhamer, Matthias Hein, A. Taylan Cemgil:
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses. ICML 2022: 4421-4435 - [i23]João Carreira, Skanda Koppula, Daniel Zoran, Adrià Recasens, Catalin Ionescu, Olivier J. Hénaff, Evan Shelhamer, Relja Arandjelovic, Matthew M. Botvinick, Oriol Vinyals, Karen Simonyan, Andrew Zisserman, Andrew Jaegle:
Hierarchical Perceiver. CoRR abs/2202.10890 (2022) - [i22]Francesco Croce, Sven Gowal, Thomas Brunner, Evan Shelhamer, Matthias Hein, A. Taylan Cemgil:
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses. CoRR abs/2202.13711 (2022) - [i21]Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic:
Object discovery and representation networks. CoRR abs/2203.08777 (2022) - [i20]Jin Gao, Jialing Zhang, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang:
Back to the Source: Diffusion-Driven Test-Time Adaptation. CoRR abs/2207.03442 (2022) - [i19]Skanda Koppula, Yazhe Li, Evan Shelhamer, Andrew Jaegle, Nikhil Parthasarathy, Relja Arandjelovic, João Carreira, Olivier J. Hénaff:
Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods. CoRR abs/2209.15589 (2022) - 2021
- [c13]Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno A. Olshausen, Trevor Darrell:
Tent: Fully Test-Time Adaptation by Entropy Minimization. ICLR 2021 - [i18]Zhuang Liu, Trevor Darrell, Evan Shelhamer:
Confidence Adaptive Anytime Pixel-Level Recognition. CoRR abs/2104.00749 (2021) - [i17]Dequan Wang, An Ju, Evan Shelhamer, David A. Wagner, Trevor Darrell:
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks. CoRR abs/2105.08714 (2021) - [i16]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR abs/2107.14795 (2021) - [i15]Dequan Wang, Shaoteng Liu, Sayna Ebrahimi, Evan Shelhamer, Trevor Darrell:
On-target Adaptation. CoRR abs/2109.01087 (2021) - 2020
- [i14]Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno A. Olshausen, Trevor Darrell:
Fully Test-time Adaptation by Entropy Minimization. CoRR abs/2006.10726 (2020) - [i13]Mark Hamilton, Evan Shelhamer, William T. Freeman:
It Is Likely That Your Loss Should be a Likelihood. CoRR abs/2007.06059 (2020)
2010 – 2019
- 2019
- [c12]Kelsey R. Allen, Evan Shelhamer, Hanul Shin, Joshua B. Tenenbaum:
Infinite Mixture Prototypes for Few-shot Learning. ICML 2019: 232-241 - [i12]Kelsey R. Allen, Evan Shelhamer, Hanul Shin, Joshua B. Tenenbaum:
Infinite Mixture Prototypes for Few-Shot Learning. CoRR abs/1902.04552 (2019) - [i11]Evan Shelhamer, Dequan Wang, Trevor Darrell:
Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields. CoRR abs/1904.11487 (2019) - [i10]Dequan Wang, Evan Shelhamer, Bruno A. Olshausen, Trevor Darrell:
Dynamic Scale Inference by Entropy Minimization. CoRR abs/1908.03182 (2019) - 2018
- [c11]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. CVPR Workshops 2018: 2050-2053 - [c10]Fisher Yu, Dequan Wang, Evan Shelhamer, Trevor Darrell:
Deep Layer Aggregation. CVPR 2018: 2403-2412 - [c9]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. ICLR 2018 - [c8]Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alyosha A. Efros, Sergey Levine:
Conditional Networks for Few-Shot Semantic Segmentation. ICLR (Workshop) 2018 - [c7]Fisher Yu, Dequan Wang, Evan Shelhamer, Trevor Darrell:
Learning Rich Image Representation with Deep Layer Aggregation. ICLR (Workshop) 2018 - [i9]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. CoRR abs/1804.08606 (2018) - [i8]Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alexei A. Efros, Sergey Levine:
Few-Shot Segmentation Propagation with Guided Networks. CoRR abs/1806.07373 (2018) - 2017
- [j1]Evan Shelhamer, Jonathan Long, Trevor Darrell:
Fully Convolutional Networks for Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(4): 640-651 (2017) - [c6]Evan Shelhamer, Parsa Mahmoudieh, Max Argus, Trevor Darrell:
Loss is its own Reward: Self-Supervision for Reinforcement Learning. ICLR (Workshop) 2017 - 2016
- [c5]Evan Shelhamer, Kate Rakelly, Judy Hoffman, Trevor Darrell:
Clockwork Convnets for Video Semantic Segmentation. ECCV Workshops (3) 2016: 852-868 - [i7]Evan Shelhamer, Jonathan Long, Trevor Darrell:
Fully Convolutional Networks for Semantic Segmentation. CoRR abs/1605.06211 (2016) - [i6]Evan Shelhamer, Kate Rakelly, Judy Hoffman, Trevor Darrell:
Clockwork Convnets for Video Semantic Segmentation. CoRR abs/1608.03609 (2016) - [i5]Evan Shelhamer, Parsa Mahmoudieh, Max Argus, Trevor Darrell:
Loss is its own Reward: Self-Supervision for Reinforcement Learning. CoRR abs/1612.07307 (2016) - 2015
- [c4]Jonathan Long, Evan Shelhamer, Trevor Darrell:
Fully convolutional networks for semantic segmentation. CVPR 2015: 3431-3440 - [c3]Evan Shelhamer, Jonathan T. Barron, Trevor Darrell:
Scene Intrinsics and Depth from a Single Image. ICCV Workshops 2015: 235-242 - [c2]Deepak Pathak, Evan Shelhamer, Jonathan Long, Trevor Darrell:
Fully Convolutional Multi-Class Multiple Instance Learning. ICLR (Workshop) 2015 - [i4]Ning Zhang, Evan Shelhamer, Yang Gao, Trevor Darrell:
Fine-grained pose prediction, normalization, and recognition. CoRR abs/1511.07063 (2015) - 2014
- [c1]Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross B. Girshick, Sergio Guadarrama, Trevor Darrell:
Caffe: Convolutional Architecture for Fast Feature Embedding. ACM Multimedia 2014: 675-678 - [i3]Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross B. Girshick, Sergio Guadarrama, Trevor Darrell:
Caffe: Convolutional Architecture for Fast Feature Embedding. CoRR abs/1408.5093 (2014) - [i2]Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer:
cuDNN: Efficient Primitives for Deep Learning. CoRR abs/1410.0759 (2014) - [i1]Jonathan Long, Evan Shelhamer, Trevor Darrell:
Fully Convolutional Networks for Semantic Segmentation. CoRR abs/1411.4038 (2014)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-02-15 00:18 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
