176 research outputs found
Distilling Inter-Class Distance for Semantic Segmentation
Knowledge distillation is widely adopted in semantic segmentation to reduce
the computation cost.The previous knowledge distillation methods for semantic
segmentation focus on pixel-wise feature alignment and intra-class feature
variation distillation, neglecting to transfer the knowledge of the inter-class
distance in the feature space, which is important for semantic segmentation. To
address this issue, we propose an Inter-class Distance Distillation (IDD)
method to transfer the inter-class distance in the feature space from the
teacher network to the student network. Furthermore, semantic segmentation is a
position-dependent task,thus we exploit a position information distillation
module to help the student network encode more position information. Extensive
experiments on three popular datasets: Cityscapes, Pascal VOC and ADE20K show
that our method is helpful to improve the accuracy of semantic segmentation
models and achieves the state-of-the-art performance. E.g. it boosts the
benchmark model("PSPNet+ResNet18") by 7.50% in accuracy on the Cityscapes
dataset.Comment: IJCAI-ECAI2022 Long Ora
Study and Prospects: Adaptive Planning and Control of Supply Chain in One-of-a-kind Production
Based on the research project titled “Adaptive Planning and Control of Supply Chain in One-of-a-kind Production”, the research group performed a systematic review of supply chain integration, risk prediction and control and trace ability. Studies of a computer-aided and integrated production system for cost-effective OKP systemare included. Our efforts relevant to integration of supply chain in OKP, modeling &control of ripple effects in OKP supply chain and the trace ability of the OKP supply chain are introduced in this paper
PHRIT: Parametric Hand Representation with Implicit Template
We propose PHRIT, a novel approach for parametric hand mesh modeling with an
implicit template that combines the advantages of both parametric meshes and
implicit representations. Our method represents deformable hand shapes using
signed distance fields (SDFs) with part-based shape priors, utilizing a
deformation field to execute the deformation. The model offers efficient
high-fidelity hand reconstruction by deforming the canonical template at
infinite resolution. Additionally, it is fully differentiable and can be easily
used in hand modeling since it can be driven by the skeleton and shape latent
codes. We evaluate PHRIT on multiple downstream tasks, including
skeleton-driven hand reconstruction, shapes from point clouds, and single-view
3D reconstruction, demonstrating that our approach achieves realistic and
immersive hand modeling with state-of-the-art performance.Comment: Accepted by ICCV202
Virosome, a hybrid vehicle for efficient and safe drug delivery and its emerging application in cancer treatment
A virosome is an innovative hybrid drug delivery system with advantages of both viral and non-viral vectors. Studies have shown that a virosome can carry various biologically active molecules, such as nucleic acids, peptides, proteins and small organic molecules. Targeted drug delivery using virosome-based systems can be achieved through surface modifications of virosomes. A number of virosome-based prophylactic and therapeutic products with high safety profiles are currently available in the market. Cancer treatment is a big battlefield for virosome-based drug delivery systems. This review provides an overview of the general concept, preparation procedures, working mechanisms, preclinical studies and clinical applications of virosomes in cancer treatment
TapMo: Shape-aware Motion Generation of Skeleton-free Characters
Previous motion generation methods are limited to the pre-rigged 3D human
model, hindering their applications in the animation of various non-rigged
characters. In this work, we present TapMo, a Text-driven Animation Pipeline
for synthesizing Motion in a broad spectrum of skeleton-free 3D characters. The
pivotal innovation in TapMo is its use of shape deformation-aware features as a
condition to guide the diffusion model, thereby enabling the generation of
mesh-specific motions for various characters. Specifically, TapMo comprises two
main components - Mesh Handle Predictor and Shape-aware Diffusion Module. Mesh
Handle Predictor predicts the skinning weights and clusters mesh vertices into
adaptive handles for deformation control, which eliminates the need for
traditional skeletal rigging. Shape-aware Motion Diffusion synthesizes motion
with mesh-specific adaptations. This module employs text-guided motions and
mesh features extracted during the first stage, preserving the geometric
integrity of the animations by accounting for the character's shape and
deformation. Trained in a weakly-supervised manner, TapMo can accommodate a
multitude of non-human meshes, both with and without associated text motions.
We demonstrate the effectiveness and generalizability of TapMo through rigorous
qualitative and quantitative experiments. Our results reveal that TapMo
consistently outperforms existing auto-animation methods, delivering
superior-quality animations for both seen or unseen heterogeneous 3D
characters
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion
Accurate 3D reconstruction of the hand and object shape from a hand-object
image is important for understanding human-object interaction as well as human
daily activities. Different from bare hand pose estimation, hand-object
interaction poses a strong constraint on both the hand and its manipulated
object, which suggests that hand configuration may be crucial contextual
information for the object, and vice versa. However, current approaches address
this task by training a two-branch network to reconstruct the hand and object
separately with little communication between the two branches. In this work, we
propose to consider hand and object jointly in feature space and explore the
reciprocity of the two branches. We extensively investigate cross-branch
feature fusion architectures with MLP or LSTM units. Among the investigated
architectures, a variant with LSTM units that enhances object feature with hand
feature shows the best performance gain. Moreover, we employ an auxiliary depth
estimation module to augment the input RGB image with the estimated depth map,
which further improves the reconstruction accuracy. Experiments conducted on
public datasets demonstrate that our approach significantly outperforms
existing approaches in terms of the reconstruction accuracy of objects.Comment: Accepted by IEEE Transactions on Image Processing (TIP
The accuracy of echocardiography versus surgical and pathological classification of patients with ruptured mitral chordae tendineae: a large study in a Chinese cardiovascular center
BACKGROUND: The accuracy of echocardiography versus surgical and pathological classification of patients with ruptured mitral chordae tendineae (RMCT) has not yet been investigated with a large study. METHODS: Clinical, hemodynamic, surgical, and pathological findings were reviewed for 242 patients with a preoperative diagnosis of RMCT that required mitral valvular surgery. Subjects were consecutive in-patients at Fuwai Hospital in 2002-2008. Patients were evaluated by thoracic echocardiography (TTE) and transesophageal echocardiography (TEE). RMCT cases were classified by location as anterior or posterior, and classified by degree as partial or complete RMCT, according to surgical findings. RMCT cases were also classified by pathology into four groups: myxomatous degeneration, chronic rheumatic valvulitis (CRV), infective endocarditis and others. RESULTS: Echocardiography showed that most patients had a flail mitral valve, moderate to severe mitral regurgitation, a dilated heart chamber, mild to moderate pulmonary artery hypertension and good heart function. The diagnostic accuracy for RMCT was 96.7% for TTE and 100% for TEE compared with surgical findings. Preliminary experiments demonstrated that the sensitivity and specificity of diagnosing anterior, posterior and partial RMCT were high, but the sensitivity of diagnosing complete RMCT was low. Surgical procedures for RMCT depended on the location of ruptured chordae tendineae, with no relationship between surgical procedure and complete or partial RMCT. The echocardiographic characteristics of RMCT included valvular thickening, extended subvalvular chordae, echo enhancement, abnormal echo or vegetation, combined with aortic valve damage in the four groups classified by pathology. The incidence of extended subvalvular chordae in the myxomatous group was higher than that in the other groups, and valve thickening in combination with AV damage in the CRV group was higher than that in the other groups. Infective endocarditis patients were younger than those in the other groups. Furthermore, compared other groups, the CRV group had a larger left atrium, higher aortic velocity, and a higher pulmonary arterial systolic pressure. CONCLUSIONS: Echocardiography is a reliable method for diagnosing RMCT and is useful for classification. Echocardiography can be used to guide surgical procedures and for preliminary determination of RMCT pathological types
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