3D Question Answering

Visual Question Answering (VQA) has witnessed tremendous progress in recent years. However, most efforts only focus on the 2D image question answering tasks. In this paper, we present the first attempt at extending VQA to the 3D domain, which can facilitate artificial intelligence's perception of 3D real-world scenarios. Different from image based VQA, 3D Question Answering (3DQA) takes the color point cloud as input and requires both appearance and 3D geometry comprehension ability to answer the 3D-related questions. To this end, we propose a novel transformer-based 3DQA framework "3DQA-TR", which consists of two encoders for exploiting the appearance and geometry information, respectively. The multi-modal information of appearance, geometry, and the linguistic question can finally attend to each other via a 3D-Linguistic Bert to predict the target answers. To verify the effectiveness of our proposed 3DQA framework, we further develop the first 3DQA dataset "ScanQA", which builds on the ScanNet dataset and contains $\sim$6K questions, $\sim$30K answers for $806$ scenes. Extensive experiments on this dataset demonstrate the obvious superiority of our proposed 3DQA framework over existing VQA frameworks, and the effectiveness of our major designs. Our code and dataset will be made publicly available to facilitate the research in this direction.Comment: To Appear at IEEE Transactions on Visualization and Computer Graphics (TVCG) 202

Enrichment and characteristics of ammonia-oxidizing archaea in wastewater treatment process

High purity ammonia-oxidizing archaea (AOA) culture containing a single AOA strain was enriched from the filtering materials of biological aerated filter. The concentration of AOA reached 3.27\ua0×\ua010\ua0copies/mL, while its proportion was 91.40%. The AOA amoA gene sequence belonged to Nitrososphaera cluster. Ammonia concentration significantly influenced the growth of AOA in culture, while total organic carbon (TOC) concentration had no obvious effect. The optimum ammonia concentration, temperature, pH and DO concentration for growth of AOA were 1\ua0mM, 30\ua0°C, 7.5 and 2.65\ua0mg/L, respectively. Under the optimum growth conditions, the AOA abundance and ammonia oxidation rate were 3.53\ua0×\ua010\ua0copies/mL and 2.54\ua0×\ua010\ua0mg/(copies·d)

Semantic Interpretation of Superlative Expressions via Structured Knowledge Bases

This paper addresses a novel task of se-mantically analyzing the comparative con-structions inherent in attributive superla-tive expressions against structured knowl-edge bases (KBs). The task can be de-fined in two-fold: first, selecting the com-parison dimension against a KB, on which the involved items are compared; and sec-ond, determining the ranking order, in which the items are ranked (ascending or descending). We exploit Wikipedia and Freebase to collect training data in an un-supervised manner, where a neural net-work model is then learnt to select, from Freebase predicates, the most appropriate comparison dimension for a given superla-tive expression, and further determine its ranking order heuristically. Experimen-tal results show that it is possible to learn from coarsely obtained training data to semantically characterize the comparative constructions involved in attributive su-perlative expressions. ? 2015 Association for Computational Linguistics.EI225-230

M3D-VTON: A Monocular-to-3D Virtual Try-On Network

Virtual 3D try-on can provide an intuitive and realistic view for online shopping and has a huge potential commercial value. However, existing 3D virtual try-on methods mainly rely on annotated 3D human shapes and garment templates, which hinders their applications in practical scenarios. 2D virtual try-on approaches provide a faster alternative to manipulate clothed humans, but lack the rich and realistic 3D representation. In this paper, we propose a novel Monocular-to-3D Virtual Try-On Network (M3D-VTON) that builds on the merits of both 2D and 3D approaches. By integrating 2D information efficiently and learning a mapping that lifts the 2D representation to 3D, we make the first attempt to reconstruct a 3D try-on mesh only taking the target clothing and a person image as inputs. The proposed M3D-VTON includes three modules: 1) The Monocular Prediction Module (MPM) that estimates an initial full-body depth map and accomplishes 2D clothes-person alignment through a novel two-stage warping procedure; 2) The Depth Refinement Module (DRM) that refines the initial body depth to produce more detailed pleat and face characteristics; 3) The Texture Fusion Module (TFM) that fuses the warped clothing with the non-target body part to refine the results. We also construct a high-quality synthesized Monocular-to-3D virtual try-on dataset, in which each person image is associated with a front and a back depth map. Extensive experiments demonstrate that the proposed M3D-VTON can manipulate and reconstruct the 3D human body wearing the given clothing with compelling details and is more efficient than other 3D approaches

Effects of particle size of zero-valent iron (ZVI) on peroxydisulfate-ZVI enhanced sludge dewaterability

The advanced oxidization process has proven to be an effective conditioning technique for the improvement of sludge dewaterability. Zero-valent iron (ZVI) is often used as the catalyst of the oxidization process. This study applied ZVI with different particle sizes to the ZVI- peroxydisulfate reactions, and investigated their effects on the improvement of sludge dewaterability. It was found that ZVI particles with smaller sizes (100 and 400 meshes) led to slightly higher enhancement of sludge dewaterability (69.1%-72%) than the larger size particles (20-40 meshes) with the reduction rate of CST by 64%. However, after the treatment, the recycle rate of larger size ZVI particles was obviously higher than the small sizes ZVI particles: 98.3% vs. 87.6-89.7%. Different surface areas of the ZVI particles with different sizes might contribute to the phenomenon. For the small ZVI particles with the sizes of 100 and 400 meshes, no obvious differences of oxidization effects and the improvements of sludge dewaterability were found between them, which might be because an oxide layer could have been formed on the surface of fine ZVI particles and led to agglomeration. According to the economical analysis, the small particles (100 and 400 meshes) of ZVI were more economically favorable for the oxidative conditioning process with ZVI-peroxydisulfate than large ZVI particles (20-40 meshes)

Three-Dimensional Graphene Structure for Healable Flexible Electronics Based on Diels–Alder Chemistry

Wearable electronics with excellent stretchability and sensitivity have emerged as a very promising field with wide applications such as e-skin and human motion detection. Although three-dimensional (3D) graphene structures (GS) have been reported for high-performance strain sensors, challenges still remain such as the high cost of GS preparation, low stretchability, and the lack of ability to heal itself. In this paper, we reported a novel self-healing flexible electronics with 3D GS based on Diels–Alder (DA) chemistry. Furfurylamine (FA) was employed as a reducing as well as a modifying agent, forming GS by FA (FAGS)/DA bonds contained polyurethane with the “infiltrate-gel-dry” process. The as-prepared composite exhibited excellent stretchability (200%) and intrinsic conductivity with low incorporation of graphene (about 2 wt %), which could be directly employed for flexible electronics to detect human motions. Besides, the FAGS/DAPU composite exhibited lower temperature retro-DA response for the continuous graphene networks. Highly effective healing of the composites by heat and microwave has been demonstrated successfully