René's URL Explorer Experiment


Title: Christoph Feichtenhofer

direct link

Domain: feichtenhofer.github.io

NoneIE=edge

Links:

https://github.com/feichtenhofer
http://linkedin.com/in/christoph-feichtenhofer-549433a1
http://scholar.google.com/citations?user=UxuqG1EAAAAJ
Google Scholar https://scholar.google.com/citations?user=UxuqG1EAAAAJ
paperhttps://ai.meta.com/research/publications/sam-3-segment-anything-with-concepts/
websitehttps://ai.meta.com/sam3/
demohttps://aidemos.meta.com/segment-anything/gallery
bloghttps://ai.meta.com/blog/segment-anything-model-3/
codehttps://github.com/facebookresearch/sam3
arXivhttps://arxiv.org/abs/2512.18099
websitehttps://ai.meta.com/research/samaudio/
demohttps://aidemos.meta.com/segment-anything/editor/segment-audio
codehttps://github.com/facebookresearch/sam-audio
arXivhttps://arxiv.org/abs/2512.19687
codehttps://github.com/facebookresearch/perception_models
arXivhttps://arxiv.org/abs/2504.13181
codehttps://github.com/facebookresearch/perception_models/blob/main/apps/pe/README.md
datahttps://ai.meta.com/datasets/pe-video/
arXivhttps://arxiv.org/abs/2504.13180
codehttps://github.com/facebookresearch/perception_models/blob/main/apps/plm/README.md
datahttps://ai.meta.com/datasets/plm-data/
SAM 3https://ai.meta.com/sam3
herehttps://aidemos.meta.com/segment-anything/gallery
ICLR Best Paper Honorable Mention Awardhttps://blog.iclr.cc/2025/04/22/announcing-the-outstanding-paper-awards-at-iclr-2025/
Perception Encoder & Perception Language Modelhttps://ai.meta.com/blog/meta-fair-updates-perception-localization-reasoning/
Visual object tracking and segmentation challenge VOTS2024 workshophttps://www.votchallenge.net/vots2024/program.html
OmniLabel Workshophttps://sites.google.com/view/omnilabel-workshop-eccv24/program
Doctoral Consortiumhttps://eccv.ecva.net/Conferences/2024/CallForDoctoralConsortium
SAM 2https://ai.meta.com/sam2
Llama 3https://llama.meta.com/
demohttps://sam2.metademolab.com/
Computer Vision with Humans in the Loophttps://cvhl.org/
Efficient Large Vision Modelshttps://sites.google.com/view/elvm/home
Doctoral Consortiumhttps://cvpr.thecvf.com/Conferences/2024/CallForDoctoralConsortium
PAMI Young Researcher Awardhttps://tc.computer.org/tcpami/2022/08/22/pami-young-researcher-award
Video AI Symposiumhttps://dimadamen.github.io/VideoAI2023/
Self-Supervised Representation Learning in Computer Visionhttps://feichtenhofer.github.io/iccv2023-ssl-tutorial/
New Ideas in Vision Transformers Workshophttps://sites.google.com/view/nivt-iccv2023/
Self-Supervised Learning in Vision: from Research Advances to Best Practiceshttps://icml.cc/virtual/2023/events/tutorial
Self-Supervised Representation Learning in Computer Visionhttps://feichtenhofer.github.io/eccv2022-ssl-tutorial/
Ego4D Workshophttps://ego4d-data.org/workshops/eccv22/
LatinX in CV Workshophttps://www.latinxinai.org/eccv-2022
Efficient Video Understanding: State-of-the-art, Challenges, and Opportunitieshttps://sites.google.com/view/effvideo-2021/
Doctoral Consortiumhttps://iccv2021.thecvf.com/doctoral-consortium
Social Events https://iccv2021.thecvf.com/networking-sessions
PyTorchVideohttps://pytorchvideo.org/
Visual Recognition for Images, Video, and 3Dhttps://s9xie.github.io/Tutorials/ECCV2020/
Images, Video, and 3Dhttp://s9xie.github.io/Tutorials/CVPR2020/
Large Scale Holistic Video Understanding Tutorialhttps://holistic-video-understanding.github.io/tutorials/cvpr2020.html
International Challenge on Activity Recognition (ActivityNet)http://activity-net.org/challenges/2020/
Language & Vision with applications to Video Understandinghttps://languageandvision.github.io/
Images, Video, and 3Dhttps://alexander-kirillov.github.io/tutorials/visual-recognition-iccv19/
venturebeat article: "Facebook’s SlowFast video classifier AI was inspired by primate eyes"https://venturebeat.com/2019/11/04/facebooks-slowfast-video-classifier-ai-was-inspired-by-primate-eyes/
PySlowFasthttps://github.com/facebookresearch/SlowFast
AVA video activity detection http://research.google.com/ava/challenge.html
International Challenge on Activity Recognition (ActvityNet) http://activity-net.org/challenges/2019/
SlowFast https://arxiv.org/abs/1812.03982
AVA Challenge report http://static.googleusercontent.com/media/research.google.com/en//ava/2019/fair_slowfast.pdf
SlowFast https://arxiv.org/abs/1812.03982
Visual Recognitionhttp://feichtenhofer.github.io/cvpr2019-recognition-tutorial/
Action Classification and Video Modellinghttps://actionclassification-videomodelling.github.io/
International Conference on Predictive Vision http://cvr.yorku.ca/conference2019/program
Visual Recognitionhttps://gkioxari.github.io/Tutorials/eccv2018/index.html
Meta Superintelligence Labshttps://ai.meta.com/research/
FAIRhttps://ai.meta.com/research/
VGGhttp://www.robots.ox.ac.uk/~vgg/
EMShttps://www.tugraz.at/en/institutes/emt/home/
Vision Labhttp://vision.eecs.yorku.ca/main/
Dynamic Scene Recognition with Oriented Spacetime Energieshttps://feichtenhofer.github.io/pubs/Feichtenhofer_MScThesis_5Nov13.pdf
Vision Labhttp://vision.eecs.yorku.ca/main/
No-Reference Sharpness Metric based on Local Gradient Analysishttps://feichtenhofer.github.io/pubs/BSc_thesis_feichtenhofer_sharpness_10-2011.pdf
Google Scholar https://scholar.google.com/citations?user=UxuqG1EAAAAJ
arXivhttps://arxiv.org/abs/2408.00714
websitehttps://ai.meta.com/sam2/
demohttps://sam2.metademolab.com/
bloghttps://ai.meta.com/blog/segment-anything-2-video/
codehttps://github.com/facebookresearch/sam2
arXivhttps://arxiv.org/abs/2501.05453
websitehttps://brjathu.github.io/toto/
arXivhttps://arxiv.org/abs/2407.21783
websitehttps://llama.meta.com/
bloghttps://ai.meta.com/blog/meta-llama-3-1/
codehttps://github.com/meta-llama/llama-models
arXivhttps://arxiv.org/abs/2309.16671
codehttps://github.com/facebookresearch/MetaCLIP
arXivhttps://arxiv.org/abs/2311.05613
codehttps://github.com/facebookresearch/hiera
arXivhttps://arxiv.org/abs/2306.00989
codehttps://github.com/facebookresearch/hiera
arXivhttps://arxiv.org/abs/2212.08071
codehttps://github.com/facebookresearch/mavil
arXivhttps://arxiv.org/abs/2304.03283
websitehttps://weichen582.github.io/diffmae.html
arXivhttps://arxiv.org/abs/2301.02241
codehttps://github.com/facebookresearch/CiT
arXivhttps://arxiv.org/abs/2303.13496
codehttps://github.com/facebookresearch/maws/
arXivhttps://arxiv.org/abs/2212.00794
codehttps://github.com/facebookresearch/flip
arXivhttps://arxiv.org/abs/2301.08247
websitehttps://mcc3d.github.io/
codehttps://github.com/facebookresearch/MCC
arXivhttps://arxiv.org/abs/2210.09461
Meta AI bloghttps://research.facebook.com/blog/2023/2/token-merging-your-vit-but-faster/
codehttps://github.com/facebookresearch/ToMe
arXivhttps://arxiv.org/abs/2205.09113
codehttps://github.com/facebookresearch/SlowFast/tree/main/projects/mae
PySlowFasthttps://github.com/facebookresearch/SlowFast
PyTorchVideohttps://github.com/facebookresearch/pytorchvideo
arXivhttps://arxiv.org/abs/2207.06405
codehttps://github.com/facebookresearch/AudioMAE
arXivhttps://arxiv.org/abs/2201.08383
codehttps://github.com/facebookresearch/SlowFast
PySlowFasthttps://github.com/facebookresearch/SlowFast
PyTorchVideohttps://github.com/facebookresearch/pytorchvideo
arXivhttps://arxiv.org/abs/2112.09133
codehttps://github.com/facebookresearch/SlowFast/tree/main/projects/maskfeat
PySlowFasthttps://github.com/facebookresearch/SlowFast
PyTorchVideohttps://github.com/facebookresearch/pytorchvideo
arXivhttps://arxiv.org/abs/2112.01526
codehttps://github.com/facebookresearch/mvit
arXivhttps://arxiv.org/abs/2302.04869
websitehttps://karttikeya.github.io/publication/revvit/
codehttps://github.com/facebookresearch/SlowFast
min codehttps://github.com/karttikeya/minREV
arXivhttps://arxiv.org/abs/2201.03545
codehttps://github.com/facebookresearch/ConvNeXt
arXivhttps://arxiv.org/abs/2101.02702
codehttps://github.com/timmeinhardt/trackformer
arXivhttps://arxiv.org/abs/2110.07058
websitehttps://ego4d-data.org/
arXivhttps://dl.acm.org/doi/abs/10.1145/3474085.3478329
codehttps://github.com/facebookresearch/pytorchvideo
websitehttps://pytorchvideo.org/
arXivhttps://arxiv.org/abs/2104.11227
codehttps://github.com/facebookresearch/SlowFast
talkhttps://youtu.be/IG4il10zx68
PySlowFasthttps://github.com/facebookresearch/SlowFast
PyTorchVideohttps://github.com/facebookresearch/pytorchvideo
arXivhttps://arxiv.org/abs/2104.14558
codehttps://github.com/facebookresearch/SlowFast
PySlowFasthttps://github.com/facebookresearch/SlowFast
PyTorchVideo.https://github.com/facebookresearch/pytorchvideo
arXivhttps://arxiv.org/abs/2104.00682
arXivhttps://arxiv.org/abs/2109.14084
codehttps://github.com/pytorch/fairseq/tree/main/examples/MMPT
arXivhttps://arxiv.org/abs/2106.05392
codehttps://github.com/facebookresearch/Motionformer
arXivhttps://arxiv.org/abs/2105.09996
codehttps://github.com/pytorch/fairseq/tree/main/examples/MMPT
arXivhttps://arxiv.org/abs/2004.04730
codehttps://github.com/facebookresearch/SlowFast
arXivhttps://arxiv.org/abs/2001.08740
code (to be released)https://github.com/facebookresearch/SlowFast
arXivhttps://arxiv.org/abs/2004.03580
codehttps://github.com/open-mmlab/mmdetection/tree/master/mmdet/models/necks
arXivhttps://arxiv.org/abs/1912.00998
codehttps://github.com/facebookresearch/SlowFast
arXivhttps://arxiv.org/abs/2001.04583
websitehttp://vision.cs.utexas.edu/projects/ego-topo/
AVA video activity detection http://research.google.com/ava/challenge.html
PySlowFasthttps://github.com/facebookresearch/SlowFast
arXivhttps://arxiv.org/abs/1812.03982
AVA challenge reporthttp://static.googleusercontent.com/media/research.google.com/en//ava/2019/fair_slowfast.pdf
codehttps://github.com/facebookresearch/SlowFast
Facebook AI bloghttps://ai.facebook.com/blog/slowfast-video-recognition-through-dual-frame-rate-analysis/
Venturebeat articlehttps://venturebeat.com/2019/11/04/facebooks-slowfast-video-classifier-ai-was-inspired-by-primate-eyes/
talkhttps://conftube.com/video/8oUPyhwzIDo?tocitem=37
arXivhttps://arxiv.org/abs/1901.07677
code https://github.com/facebookresearch/QuaterNet
springerhttps://link.springer.com/article/10.1007/s11263-019-01245-6
arXivhttps://arxiv.org/abs/1812.04558
websitehttp://vision.cs.utexas.edu/projects/interaction-hotspots/
arXivhttps://arxiv.org/abs/1906.04016
arXivhttps://arxiv.org/abs/1812.05038
arXivhttps://arxiv.org/abs/1811.11742
code https://github.com/facebookresearch/VideoPose3D
websitehttps://dariopavllo.github.io/VideoPose3D/
IJCV paper (with animations)https://feichtenhofer.github.io/pubs/Feichtenhofer_IJCV19.pdf
CVPR paper (with animations)https://feichtenhofer.github.io/pubs/Feichtenhofer_Action_Visualization_2018.pdf
arXivhttps://arxiv.org/abs/1812.04172
paperhttps://arxiv.org/pdf/1802.07094.pdf
paperhttps://feichtenhofer.github.io/pubs/DT_iccv17.pdf
codehttps://github.com/feichtenhofer/Detect-Track
videohttps://feichtenhofer.github.io
websitehttp://www.robots.ox.ac.uk/~vgg/research/detect-track/
talkhttps://www.youtube.com/watch?v=m9GarFWuVwk
paperhttp://openaccess.thecvf.com/content_cvpr_2017/papers/Feichtenhofer_Spatiotemporal_Multiplier_Networks_CVPR_2017_paper.pdf
codehttps://github.com/feichtenhofer/st-resnet
paperhttp://openaccess.thecvf.com/content_cvpr_2017/papers/Feichtenhofer_Temporal_Residual_Networks_CVPR_2017_paper.pdf
supplementhttp://openaccess.thecvf.com/content_cvpr_2017/supplemental/Feichtenhofer_Temporal_Residual_Networks_2017_CVPR_supplemental.pdf
codehttps://github.com/feichtenhofer/temporal-resnet
paperhttps://feichtenhofer.github.io/pubs/STResNet_NIPS2016.pdf
codehttps://github.com/feichtenhofer/st-resnet
paperhttps://feichtenhofer.github.io/pubs/Feichtenhofer_Two_Stream_Fusion_2016_CVPR.pdf
codehttps://github.com/feichtenhofer/twostreamfusion
websitehttp://www.robots.ox.ac.uk/~vgg/software/two_stream_action/
posterhttps://feichtenhofer.github.io/pubs/Feichtenhofer_Two_Stream_Fusion_2016_CVPR_Poster.pdf
paperhttps://feichtenhofer.github.io/pubs/FeichtenhoferPinzWildesPAMI2016.pdf
paperhttp://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Feichtenhofer_Dynamically_Encoded_Actions_2015_CVPR_paper.pdf
paperhttps://feichtenhofer.github.io/pubs/Feichtenhofer_Bags_of_Spacetime_2014_CVPR_paper.pdf
spotlight videohttps://feichtenhofer.github.io
paperhttps://feichtenhofer.github.io/pubs/Goller_fusing_RFID_with_Vision_2014.pdf
paperhttps://feichtenhofer.github.io/pubs/spacetime_forests_BMVC13.pdf
talkhttp://videolectures.net/bmvc2013_feichtenhofer_scene_recognition/
paperhttps://feichtenhofer.github.io/pubs/Feichtenhofer_Spatio-temporal_Good_Features_2013_ICCV_paper.pdf
paperhttps://feichtenhofer.github.io/pubs/Feichtenhofer_Image_Sharpness_Metric_IEEE_SPL_2013.pdf
codehttps://github.com/feichtenhofer/PSI

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