163 research outputs found
FaceCLIPNeRF: Text-driven 3D Face Manipulation using Deformable Neural Radiance Fields
As recent advances in Neural Radiance Fields (NeRF) have enabled
high-fidelity 3D face reconstruction and novel view synthesis, its manipulation
also became an essential task in 3D vision. However, existing manipulation
methods require extensive human labor, such as a user-provided semantic mask
and manual attribute search unsuitable for non-expert users. Instead, our
approach is designed to require a single text to manipulate a face
reconstructed with NeRF. To do so, we first train a scene manipulator, a latent
code-conditional deformable NeRF, over a dynamic scene to control a face
deformation using the latent code. However, representing a scene deformation
with a single latent code is unfavorable for compositing local deformations
observed in different instances. As so, our proposed Position-conditional
Anchor Compositor (PAC) learns to represent a manipulated scene with spatially
varying latent codes. Their renderings with the scene manipulator are then
optimized to yield high cosine similarity to a target text in CLIP embedding
space for text-driven manipulation. To the best of our knowledge, our approach
is the first to address the text-driven manipulation of a face reconstructed
with NeRF. Extensive results, comparisons, and ablation studies demonstrate the
effectiveness of our approach.Comment: ICCV 202
Inference of Gene Regulatory Networks Using Time-Series Data: A Survey
The advent of high-throughput technology like microarrays has provided the platform for studying how different cellular components work together, thus created an enormous interest in mathematically modeling biological network, particularly gene regulatory network (GRN). Of particular interest is the modeling and inference on time-series data, which capture a more thorough picture of the system than non-temporal data do. We have given an extensive review of methodologies that have been used on time-series data. In realizing that validation is an impartible part of the inference paradigm, we have also presented a discussion on the principles and challenges in performance evaluation of different methods. This survey gives a panoramic view on these topics, with anticipation that the readers will be inspired to improve and/or expand GRN inference and validation tool repository
Lamellar keratoplasty using position-guided surgical needle and M-mode optical coherence tomography
Deep anterior lamellar keratoplasty (DALK) is an emerging surgical technique for the restoration of corneal clarity and vision acuity. The big-bubble technique in DALK surgery is the most essential procedure that includes the air injection through a thin syringe needle to separate the dysfunctional region of the cornea. Even though DALK is a well-known transplant method, it is still challenged to manipulate the needle inside the cornea under the surgical microscope, which varies its surgical yield. Here, we introduce the DALK protocol based on the position-guided needle and M-mode optical coherence tomography (OCT). Depth-resolved 26-gage needle was specially designed, fabricated by the stepwise transitional core fiber, and integrated with the swept source OCT system. Since our device is feasible to provide both the position information inside the cornea as well as air injection, it enables the accurate management of bubble formation during DALK. Our results show that real-time feedback of needle end position was intuitionally visualized and fast enough to adjust the location of the needle. Through our research, we realized that position-guided needle combined with M-mode OCT is a very efficient and promising surgical tool, which also to enhance the accuracy and stability of DALK
Bobsleigh start interval times and three-dimensional motion analysis of the lower limb joints in preparation for the 2018 Pyeongchang Winter Olympics
This study aimed to provide data to improve the technique of Korean bobsledders. To this end, we measured the start interval times of bobsledders with different performance levels and performed a motion analysis of the lower limb joints during the start interval. We divided 12 Korean bobsledders into a superior group and an inferior group before measuring the interval times and performing the motion analysis of the lower limb joints at the start of the bobsleigh. The start interval times showed a statistically significant difference between the superior and inferior groups (p \u3c .05). The motion analysis of the lower limb joints revealed significant differences in hip flexion and extension, and in ankle dorsiflexion, plantar flexion, and supination (p \u3c .05). Based on these differences, we deduced that the superior bobsledders achieved superior start times by using movements that focus more on horizontal changes in the center of gravity than on vertical changes, and movements that facilitate a longer stride
Gypsum-Dependent Effect of NaCl on Strength Enhancement of CaO-Activated Slag Binders
This study explores the combined effect of NaCl and gypsum on the strength of the CaO-activated ground-granulated blast furnace slag (GGBFS) binder system. In the CaO-activated GGBFS system, the incorporation of NaCl without gypsum did not improve the strength of the system. However, with the presence of gypsum, the use of NaCl yielded significantly greater strength than the use of either gypsum or NaCl alone. The presence of NaCl largely increases the solubility of gypsum in a solution, leading to a higher concentration of sulfate ions, which is essential for generating more and faster formations of ettringite in a fresh mixture of paste. The significant strength enhancement of gypsum was likely due to the accelerated and increased formation of ettringite, accompanied by more efficient filling of pores in the system
Unveiling new stable manganese based photoanode materials via theoretical high-throughput screening and experiments
With the increasing energy demand, developing renewable fuel production strategies such as photoelectrocatalytic hydrogen production is critical to mitigating the global climate change. In this work, we experimentally validate a new stable and photoactive material, Mg₂MnO₄, from the exhaustive theoretical exploration of the chemical space of X (=Mg and Ca), Mn and O
In-silico interaction-resolution pathway activity quantification and application to identifying cancer subtypes
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