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Who Left the Dogs Out?3D Animal Reconstruction with Expectation ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2020-ECCV-3D-dog-reconstruction.pdf28 Jun 2021: 3. We use easily obtained 2D annotations in training, and none at test time. ... or rely heavily on input 2Dkeypoints or video at test-time [31, 28]. -
Who Left the Dogs Out?3D Animal Reconstruction with Expectation ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2020-ECCV-3D-dog-reconstruction.pdf28 Jun 2021: 3. We use easily obtained 2D annotations in training, and none at test time. ... or rely heavily on input 2Dkeypoints or video at test-time [31, 28]. Results that match 1 of 2 words
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ANALYSING BIAS IN SPOKEN LANGUAGE ASSESSMENT USINGCONCEPT ACTIVATION…
mi.eng.cam.ac.uk/~mjfg/ALTA/publications/wei_ICASSP2021.pdf22 Jul 2021: In addition, therecording conditions and levels of background noise can vary con-siderably across countries and test centres. ... Scores for each sec-tion of the test were generated by trained graders, operating withinlocal test centers. -
FootNet: An Efficient Convolutional Network forMultiview 3D Foot…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2020-ACCV-CNN-foot-reconstruction.pdf28 Jun 2021: Table 3: Average length and width errors (mm) on real val/test data. ... Pool at test timePredicted segmentation Hand segmentationLength error Width error Length error Width error. -
Efficient Large-Scale Semantic VisualLocalization in 2D Maps Tomas…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2020-ACCV-Large-scale-localization.pdf28 Jun 2021: At test time, this embedding is extractedfrom a panoramic building instance label and depth images. ... database of embeddings of the test environmentlocations to retrieve the most similar location. -
Embodied Visual Navigation With Automatic Curriculum Learning in Real …
mi.eng.cam.ac.uk/~cipolla/publications/article/2021-RA-embodied-visual-navigation.pdf28 Jun 2021: Plotsrepresent the mean and standard deviation of a single train/test scene over fivetrials. ... Fig. 4. (4a) Validation SPL over five trials on a single test-train environment. -
Rotation Equivariant Orientation Estimation forOmnidirectional…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2020-ACCV-Rotation-equivariant-localisation.pdf28 Jun 2021: In summary, we use all 1413 real imagesas well as their rendered counterparts as test data. ... We test on two versions oftest data: one with original orientations and one with random orientations. -
FootNet: An Efficient Convolutional Network forMultiview 3D Foot…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2020-ACCV-CNN-foot-reconstruction.pdf28 Jun 2021: Table 3: Average length and width errors (mm) on real val/test data. ... Pool at test timePredicted segmentation Hand segmentationLength error Width error Length error Width error. -
Efficient Large-Scale Semantic VisualLocalization in 2D Maps Tomas…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2020-ACCV-Large-scale-localization.pdf28 Jun 2021: At test time, this embedding is extractedfrom a panoramic building instance label and depth images. ... database of embeddings of the test environmentlocations to retrieve the most similar location. -
Embodied Visual Navigation With Automatic Curriculum Learning in Real …
mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2021-RA-embodied-visual-navigation.pdf28 Jun 2021: Plotsrepresent the mean and standard deviation of a single train/test scene over fivetrials. ... Fig. 4. (4a) Validation SPL over five trials on a single test-train environment.
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