Rigidity controllable as-rigid-as-possible shape deformations

Shape deformation is one of the fundamental techniques in geometric processing. One principle of deformation is to preserve the geometric details while distributing the necessary distortions uniformly. To achieve this, state-of-the-art techniques deform shapes in a locally as-rigid-as-possible (ARAP) manner. Existing ARAP deformation methods optimize rigid transformations in the 1-ring neighborhoods and maintain the consistency between adjacent pairs of rigid transformations by single overlapping edges. In this paper, we make one step further and propose to use larger local neighborhoods to enhance the consistency of adjacent rigid transformations. This is helpful to keep the geometric details better and distribute the distortions more uniformly. Moreover, the size of the expanded local neighborhoods provides an intuitive parameter to adjust physical stiffness. The larger the neighborhood is, the more rigid the material is. Based on these, we propose a novel rigidity controllable mesh deformation method where shape rigidity can be flexibly adjusted. The size of the local neighborhoods can be learned from datasets of deforming objects automatically or specified by the user, and may vary over the surface to simulate shapes composed of mixed materials. Various examples are provided to demonstrate the effectiveness of our method

Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoning

A backdoored deep hashing model is expected to behave normally on original query images and return the images with the target label when a specific trigger pattern presents. To this end, we propose the confusing perturbations-induced backdoor attack (CIBA). It injects a small number of poisoned images with the correct label into the training data, which makes the attack hard to be detected. To craft the poisoned images, we first propose the confusing perturbations to disturb the hashing code learning. As such, the hashing model can learn more about the trigger. The confusing perturbations are imperceptible and generated by optimizing the intra-class dispersion and inter-class shift in the Hamming space. We then employ the targeted adversarial patch as the backdoor trigger to improve the attack performance. We have conducted extensive experiments to verify the effectiveness of our proposed CIBA. Our code is available at https://github.com/KuofengGao/CIBA.Comment: Accepted by BMVC 202

Depletion of Tissue-Specific Ion Transporters Causes Differential Expression of PRL Targets in Response to Increased Levels of Endogenous PRL

Prolactin (PRL) has been considered a key regulator of ion uptake in zebrafish. The genes slc12a10.2 and slc12a3, which are Na+ and chloride Cl− co-transporters, have been reported to be regulated by PRL in freshwater fish. The integrative network of PRL signaling dissected from the knockout of tissue-specific downstream PRL ion transporters remains poor. In the present study, zebrafish models with increased endogenous levels of PRL were generated through the knockout of slc12a10.2 or slc12a3, and the developmental consequences were analyzed. The increased levels of pituitary PRL were observed in both slc12a10.2- and slc12a3-deficient fish. Unlike the slc12a3-deficient fish, which could survive to adulthood, the slc12a10.2-deficient fish began to die at 9 days post-fertilization (dpf) and did not survive beyond 17 dpf. This survival defect is a result of defective Cl− uptake in this mutant, indicating that Slc12a10.2 plays an essential role in Cl− uptake. Intriguingly, compared to the levels in control fish, no significant differences in the levels of Na+ in the body were observed in slc12a10.2- or slc12a3-deficient zebrafish. The upregulations of the PRL downstream transporters, slc9a3.2, slc12a10.2, and atp1a1a.5 were observed in slc12a3-deficient fish in both the gills/skin and the pronephric duct. However, this type of response was not observed in the pronephric duct of slc12a10.2-deficient fish, except under Na+-deprived conditions. Our results show that PRL is susceptible to deficiencies in downstream ion transporters. Moreover, both the gills/skin and pronephric duct show differential expression of downstream PRL targets in response to increased levels of pituitary PRL caused by the depletion of tissue-specific ion transporters

A Unified Geometric Model of Repeating and Non-Repeating Fast Radio Bursts

Fast radio bursts (FRBs) are millisecond-duration extragalactic radio transients. They apparently fall into repeaters and non-repeaters. However, such a classification has lacked a motivation on the physical picture. Here we propose a unified geometric model to distinguish between the repeaters and non-repeaters, in which the quasi-tangential (QT) propagation effect within the magnetospheric polar cap of a neutron star is considered. In this model, the non-repeaters arise from the sources whose emitting region has a smaller impact angle with respect to the magnetic axis, while the repeaters come from the sources whose emitting region has a larger impact angle. The observational discriminant polarization properties between the repeaters and non-repeaters are an important clue to verifying this unified geometric model since the polarization is sensitive to the QT propagation effect. Moreover, our model effectively explains all of the other discriminant properties, including bandwidth, duration, peak luminosity, energy, brightness temperature, time-frequency downward drifting, and repetition rate, providing compelling evidence for the magnetospheric origin of FRBs.Comment: 16 pages, 8 figure

Efficient and flexible deformation representation for data-driven surface modeling

Effectively characterizing the behavior of deformable objects has wide applicability but remains challenging. We present a new rotation-invariant deformation representation and a novel reconstruction algorithm to accurately reconstruct the positions and local rotations simultaneously. Meshes can be very efficiently reconstructed from our representation by matrix pre-decomposition, while, at the same time, hard or soft constraints can be flexibly specified with only positions of handles needed. Our approach is thus particularly suitable for constrained deformations guided by examples, providing significant benefits over state-of-the-art methods. Based on this, we further propose novel data-driven approaches to mesh deformation and non-rigid registration of deformable objects. Both problems are formulated consistently as finding an optimized model in the shape space that satisfies boundary constraints, either specified by the user, or according to the scan. By effectively exploiting the knowledge in the shape space, our method produces realistic deformation results in real-time and produces high quality registrations from a template model to a single noisy scan captured using a low-quality depth camera, outperforming state-of-the-art methods

3D face reconstruction and gaze tracking in the HMD for virtual interaction

With the rapid development of virtual reality (VR) technology, VR headsets, a.k.a. Head-Mounted Displays (HMDs), are widely available, allowing immersive 3D content to be viewed. A natural need for truly immersive VR is to allow bidirectional communication: the user should be able to interact with the virtual world using facial expressions and eye gaze, in addition to traditional means of interaction. The typical application scenario includes VR virtual conferencing and virtual roaming, where ideally users are able to see other users expressions and have eye contact with them in the virtual world. In addition, eye gaze also provides a natural means of interaction with virtual objects. Despite significant achievements in recent years for reconstruction of 3D faces from RGB or RGB-D images, it remains a challenge to reliably capture and reconstruct 3D facial expressions including eye gaze when the user is wearing an HMD, because the majority of the face is occluded, especially those areas around the eyes which are essential for recognizing facial expressions and eye gaze. In this paper, we introduce a novel real-time system that is able to capture and reconstruct 3D faces wearing HMDs, and robustly recover eye gaze. We further propose a novel method to map eye gaze directions to the 3D virtual world, which provides a novel and useful interactive mode in VR. We compare our method with state of-the-art techniques both qualitatively and quantitatively, and demonstrate the effectiveness of our system using live capture