(1) Top conference on machine learning: NIPS, ICML, UAI, AISTATS (Journal: JMLR, MIT, MIT Trends, IEEE T-NN)

Computer vision and image recognition: ICCV, CVPR, ECCV；; (Journals: IEEE T-PAMI, IJCV, IEEE T-IP)

Artificial intelligence: IJCAI, IJCAI (ai journal)

In addition, there are SIGRAPH, KDD, ACL, SIGIR, WWW and so on.

In particular, if you do machine learning, you must carefully review NIPS, ICML several times in the past four years; If you do computer vision, you should read ICCV, CVPR, Japan and ICML several times in the past four years.

(2) In addition, most papers of top conferences can be downloaded from the Internet for free.

(3) Say something about your feelings. In the field of computer vision and computational neuroscience, from the perspective of methods and models, statistical models (including probability graph models and statistical learning theories) are mainstream and very influential methods. There is a very obvious trend: important methods and models first appear in NIPS or ICML, and then apply to CV, IR and MM. Although specific problems and applications are also important, it is meaningful to pay more attention to and combine these methods.