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+has+revolutionized+visual+representation+learning%252C+but+has+not+achieved+the+robustness+of+human+vision.+A+reason+for+this+could+be+that+SSL+does+not+leverage+all+the+data+available+to+humans+during+learning.+When+learning+about+an+object%252C+humans+often+purposefully+turn+or+move+around+objects+and+research+suggests+that+these+interactions+can+substantially+enhance+their+learning.+Here+we+explore+whether+such+object-related+actions+can+boost+SSL.+For+this%252C+we+extract+the+actions+performed+to+change+from+one+ego-centric+view+of+an+object+to+another+in+four+video+datasets.+We+then+introduce+a+new+loss+function+to+learn+visual+and+action+embeddings+by+aligning+the+performed+action+with+the+representations+of+two+images+extracted+from+the+same+clip.+This+permits+the+performed+actions+to+structure+the+latent+visual+representation.+Our+experiments+show+that+our+method+consistently+outperforms+previous+methods+on+downstream+category+recognition.+In+our+analysis%252C+we+find+that+the+observed+improvement+is+associated+with+a+better+viewpoint-wise+alignment+of+different+objects+from+the+same+category.+Overall%252C+our+work+demonstrates+that+embodied+interactions+with+objects+can+improve+SSL+of+object+categories.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.ad3578add001d02c4b7e713e84f7d14a%3frik%3dstSCQis4IfaABw%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Visual+of+Supervised+Learning&FORM=IRPRST&ck=F6F4B1F8901132B4141429B795250DC1&selectedIndex=1&itb=0)
