Image2Vec: Learning word in addition to image representations as long as reasoningLerrel J. Pinto,

Image2Vec: Learning word in addition to image representations as long as reasoningLerrel J. Pinto, www.phwiki.com

Image2Vec: Learning word in addition to image representations as long as reasoningLerrel J. Pinto,

Devine, Caribe, Meteorologist has reference to this Academic Journal, PHwiki organized this Journal Image2Vec: Learning word in addition to image representations as long as reasoningLerrel J. Pinto, Gunnar A. SigurdssonHow would you summarize this image in 3 words‹ ›Joint word in addition to image embeddingGiven an image, get words that approximate‹ ›Tower+Clock+Night

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Joint word in addition to image embeddingGiven words, find an unlabeled image‹ ›Snowy+YoungCurrent embeddingsUse word similarity Learn to map images to a word spaceDoes not apply to sumsCannot recover sum of words given imageFC7 features:‹ ›-+= FormulationBe as long as e we start:If elements of x are zero except at 1, 6, 15Intuition: Each column of D is a word‹ ›OR

FormulationSimilar images = similar sumsSimilarity between images Indicator vector as long as word First solve this as long as (per image)Then solve as long as D‹ ›A black dog laying on his big dog bedFormulation (Simple model)This is a non-linear dimensionality reductionMultidimensional scaling O(N^3)Instead we use JL-Trans as long as m (adds noise) where is FC7Thus given R find D s.t. ‹ ›Models (Learn all model)To learn a better image representationLearn R too (we could backprop to deep network)(We need more constraints to do this)find D in addition to R s.t. if i in addition to j occur in same image(D,R column norm=1)‹ ›

Models (Weak tag model)To allow as long as weak tags (Flickr)Find D in addition to R s.t. s.t. s.t. if i in addition to j occur in same image(D,R column norm=1)‹ ›camping,wildernessTrainingCOCO dataset80k training images5 captions eachBuild a vocabulary from nouns in addition to adjectivesNumber of training examples, N = 400kWords as long as image are vocab words in captionModels solved withBlock coordinate descentStochastic gradient descentOrthogonal Matching Pursuit‹ ›A black dog laying on his big dog bedSummarizing image, successes‹ ›pulling+horses+grassybedroom+wooden+smallsurf+s in addition to yGiven Trained model, find words that summarize. (Sparse recovery)

Summarizing image (w2v in addition to imnet)‹ ›trombone+accordion+kimonopoodledog+rabbitice-cream+vaseblack-bear+cat+guenoncanoe+sea-lionSummarizing image (simple model)‹ ›hipster+rabbitlap+bridehipster+lambcheesecake+polkabear+hydrantwave+motorbikeSummarizing image (learn all model)‹ ›leaning+player+videotoddler+lying+livingkneeling+outsidevasebear+rocky+kneelingwet+rocky

Summarize image (weak tags model)‹ ›Be as long as e: concrete,gbr,londonAfter: crane,londonBe as long as e: diving,scubaAfter: brain-coral,scubaBe as long as e: jet,lynxAfter: airlinerThese represent successesFlickr imagesUses ImageNet in addition to Word2vecWhy is a visual model differentEnter word (break to quit): ‘yellow’Using word: yellowbus: 0.39orange: 0.32station: 0.30road: 0.28bananas: 0.27Word2Vec most similar words:Using word: yellowred: 0.75bright-yellow: 0.69orange: 0.64blue: 0.64purple: 0.63‹ ›Summary in addition to takeawaysL2 distance better than inner productAllows scaling down noisy non-visual wordsBetter optimization / learning rate / initializationPoor local minima, overfittingLearning word in addition to image embedding jointly improves summarization‹ ›bear+rocky+kneeling

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Devine, Caribe Meteorologist

Devine, Caribe is from United States and they belong to 12 News Sunday at 5:30 PM – KPNX-TV and they are from  Phoenix, United States got related to this Particular Journal. and Devine, Caribe deal with the subjects like Meteorology

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