Userful links

Major computer vision journals/conferences

Papers published (especially recently) in these venues are usually available somewhere online (mostly on the authors' website, just search the title online). In some rare cases, you might find some papers are behind a paywall. If this happens, try searching the journal/conference name (e.g. CVPR) via the UManitoba library website and accessing from there, or browing via the UManitoba library links to online digital libraries such as IEEE Xplore, ACM Digital Library, etc (see links below).

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
International Journal of Computer Vision (IJCV)
Computer Vision and Image Understanding (CVIU)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012)
IEEE International Conference on Computer Vision (ICCV 2011)
European Conference on Computer Vision (ECCV 2012)
Neural Information Processing Systems (mostly a machine learning and neuroscience conference, but also publishes good computer vision papers. The proceedings are available online.)

UManitoba library links to some important digital collections in computer science

IEEE Xplore (direct links to PAMI, CVPR, ICCV)
ACM Digital Libraries(including many journal/conference proceedings published by ACM)

Some popular datasets in computer vision (more to be added)

Object detection/recognition: PASCAL VOC, INRIA person dataset, Caltech Pedestrian dataset, Caltech 101, Caltech 256, ImageNet, LabelMe, TinyImages
Human action recognition
- Videos: KTH, Weizmann, Hollywood, Hollywood 2, UCF sports, UCF Youtube actions, HMDB
- Images: UIUC sport event, BU dataset, Stanford 40 actions, PASCAL VOC action recognition challenge
Scene recognition: MIT SUN dataset, MIT Indoor scenes, 13 natural scenes, LabelMe outdoor scenes
Datasets compiled by Kristen Grauman

Some useful software (more to be added)

Some similar courses elsewhere

Some courses on more specialized and advanced topics (mostly recognition)

Learning-based methods in vision (Alexei Efros at CMU)
Vision recognition (Kristen Grauman at UT-Austin)
Visual scene understanding (Derek Hoiem at UIUC)
Statistical models for visual recognition (Deva Ramanan at UCI)
Grounding object recognition and scene understanding (Antonio Torralba at MIT)
Recognition problems in computer vision (Greg Mori at SFU)
Object and activity recognition (Trevor Darrell at UC Berkeley)
High-level recognition (Fei-Fei Li at Stanford)
Mobile computer vision (Silvio Savarese at UMich)