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13 Mar 2018: The results are shown in the top row of Table 1 and the middle row of Fig. ... Fromtop to bottom: test image, ground truth, motion and structure inferred segmentation,and appearance inferred segmentation.

13 Mar 2018: Middle) The clusters of region trajectories computed with our algorithm are represented with differentshaded colours (some colours may be repeated). ... 1. To limit the computational load we con-sider the first 100 frames only.Our main purpose is to test

13 Mar 2018: We used 18 randomlyselected training/test combinations of the sequences forreporting identification rates. ... The test recognition rates changed byless than 1 percent for all of the different trials of randompartitioning.

13 Mar 2018: 2. Fig. 1. SegNet predictions on urban and highway scene test samples from the wild. ... 1). Some example test resultsproduced on randomly sampled road scene images from Googleare shown in Fig.

28 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].

13 Mar 2018: The class that exhibits the maximum frequency in the histogram is as-signed to the test video. ... The train/test split is around 50% and the videos arechosen as specified in [17].

13 Mar 2018: Figure 7. Sample of sparse reconstruction output. Top: a long reconstructed section; middle: close-. ... detection system and test it more extensively, comparing. the inspection performance between manual, fully-.

13 Mar 2018: Figure 1. A building façade (left), the edgels output from Canny (middle) and the resulting straightline-segments (right). ... 5 EvaluationTo test this system, a database was constructed from photographs of all the buildings in the main shoppingstreet

22 Jun 2006: The phantom included spheres of 1.5 cm, 1.0 cm and 0.5 cm diameter, in order to test theresolution of the algorithms. ... For this reason, it is not possible to use Field simulations created in thisway to test the frequency-based methods of attenuation

13 Mar 2018: 9. Adding more parts helps performance on the test data up to a. ... effect on the RP EER (up to 100N percent for N test images).

13 Mar 2018: 1.0} (1), and =0.07. |S |= 6 test scales were chosen automatically to cover the scale range in the trainingdata. ... Left: categorization performance. Middle: detectionperformance, with comparison to Opelt et al.

13 Mar 2018: We used 18 randomlyselected training/test combinations of the sequences forreporting identification rates. ... The test recognition rates changed byless than 1 percent for all of the different trials of randompartitioning.

13 Mar 2018: avoid bias), resulting in a total of 600 pairwise compar-isons per preference test. ... Scores shown as percentages of all votes for: (left) all emotions, (middle)neutral, and (right) angry.

13 Mar 2018: avoid bias), resulting in a total of 600 pairwise compar-isons per preference test. ... Scores shown as percentages of all votes for: (left) all emotions, (middle)neutral, and (right) angry.

13 Mar 2018: The imageswere randomlyandequallypartitioned intoa trainanda test set.Thetrainsetof161imageshad323frontalfacesand192profilefaces and the test set had 271 frontal and 171 profile faces. ... 184 T.-K. Kim and R. Cipolla. Fig. 17 Example tracking results on

13 Mar 2018: As closely as pos-sible, we use the same training and test sets. ... We test each class individually, pairedwith an equal number of background test images.

13 Mar 2018: The results are shown in the top row of Table 1 and the middle row of Fig. ... Fromtop to bottom: test image, ground truth, motion and structure inferred segmentation,and appearance inferred segmentation.

13 Mar 2018: because highlights are very strong and localized, so just a simplesensor saturation test is enough to find them, i.e., highlight 254. ... The next experiment was designed to test thisimprovement by performing a light estimation over K imageswhere the

11 Sep 2019: How-ever, these are not feed-forward at test time and requireoptimization to determine the MAP labels. ... We report all the threemeasures of performance at this point on the held-out Cam-Vid test set.

13 Mar 2018: Our work can be seen as a type of middle ground be-tween the domains of motion segmentation and multi-bodyfactorization. ... These would in turn preventthe “spawning” of new entity hypotheses in the middle ofthe scene.