Noshaba Cheema

"How can we animate 3D-characters from a movie script or move robots by simply telling them what we would like them to do?" "How unstructured and complex can we make a sentence and still generate plausible movements from it?" These are questions that need to be answered in the long-run, as the field is still in its infancy. Inspired by these proble...

Human motion capture data has been widely used in data-driven character animation. In order to generate realistic, natural-looking motions, most data-driven approaches require considerable efforts of pre-processing, including motion segmentation, annotation, and so on. Existing (semi-) automatic solutions either require hand-crafted features for mo...

Semantic segmentation of motion capture sequences plays a key part in many data-driven motion synthesis frameworks. It is a preprocessing step in which long recordings of motion capture sequences are partitioned into smaller segments. Afterwards, additional methods like statistical modeling can be applied to each group of structurally-similar segme...

Accurate depth maps are essential in various applications , such as autonomous driving, scene reconstruction, point-cloud creation, etc. However, monocular-depth estimation (MDE) algorithms often fail to provide enough texture & sharpness, and also are inconsistent for homogeneous scenes. These algorithms mostly use CNN or vision transformer-based...

Video depth estimation is crucial in various applications, such as scene reconstruction and augmented reality. In contrast to the naive method of estimating depths from images, a more sophisticated approach uses temporal information, thereby eliminating flickering and geometrical inconsistencies. We propose a consistent method for dense video depth...

Video super-resolution (VSR) techniques, especially deep-learning-based algorithms, have drastically improved over the last few years and shown impressive performance on synthetic data. However, their performance on real-world video data suffers because of the complexity of real-world degradations and misaligned video frames. Since obtaining a synt...

Accurate depth maps are essential in various applications, such as autonomous driving, scene reconstruction, point-cloud creation, etc. However, monocular-depth estimation (MDE) algorithms often fail to provide enough texture & sharpness, and also are inconsistent for homogeneous scenes. These algorithms mostly use CNN or vision transformer-based a...

Single-Image Super-Resolution has seen dramatic improvements due to the application of deep learning and commonly achieved results show impressive performance. Nevertheless, the applicability to real-world images is limited and expectations are often disappointed when comparing to the performance achieved on synthetic data. For improving on this as...

Natural human locomotion contains variations, which are important for creating realistic animations. Most of all when simulating a group of avatars, the resulting motions will appear robotic and not natural anymore if all avatars are simulated with the same walk cycle. While there is a lot of research work focusing on high-quality, interactive moti...

The simulation of humanoid avatars is relevant for a multitude of applications, such as movies, games, simulations for autonomous vehicles, virtual avatars and many more. In order to achieve the simulation of realistic and believable characters, it is important to simulate motion with the natural motion style matching the character’s characteristic...

User interface design for Virtual Reality and other embodied interaction contexts has to carefully consider ergonomics. A common problem is that mid-air interaction may cause excessive arm fatigue, known as the “Gorilla arm” effect. To predict and prevent such problems at a low cost, this thesis investigates user testing of mid-air interaction with...

To enable the physically correct simulation of the interaction of a 3D character with its environment the internal joint forces of a physical model of the character need to be estimated. Recently, derivative-free sampling-based optimization methods, which treat the objective function as a black box, have shown great results for finding control sign...

Human motion capture data has been widely used in data-driven character animation. In order to generate realistic, natural-looking motions, most data-driven approaches require considerable efforts of pre-processing, including motion segmentation and annotation. Existing (semi-) automatic solutions either require hand-crafted features for motion seg...

Figure 1: Our dilated temporal fully-convolutional neural network (DTFCN) for motion capture segmentation. The initial layer consists of a traditional 2D convolutional layer. The next layers are 1D temporal acausal convolutions with dilation. The final dilated conv layer uses a normalizing ReLU activation function. Finally, we add a Softmax layer a...

In the peripheral field of view our visual system provides a much lower image quality than in the central region. This has often been attributed to a mere loss of spatial acuity, but recent investigations suggest that the system uses a more refined strategy. For lowering its data load it computes a statistical summary representation based on low-le...

Representations obtained from the statistical pooling of features gain increasing popularity. The common assumption is that low-level features are best suited for such a statistical pooling. Here we investigate which level of a visual feature hierarchy can actually produce the optimal statistical representation. We make use of the award-winning VGG...

Recent studies have shown that the loss of spatial acuity and permutations (so called " crowding-effect ") in the visual periphery can be modelled using local summary-statistics. These statistical measures are based on auto-and cross-correlations, which operate on wavelet-like filter outputs. However, the neurobiological plausibility of the multipl...

Our senses can process only a limited amount of the incoming sensory information. In the human visual system this becomes apparent in the reduced performance in the peripheral field of view, as compared to the central fovea. Recent research shows that this loss of information cannot solely be attributed to a spatially coarser resolution but is esse...