35 research outputs found
Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection
Human-Object Interaction (HOI) detection is a core task for high-level image
understanding. Recently, Detection Transformer (DETR)-based HOI detectors have
become popular due to their superior performance and efficient structure.
However, these approaches typically adopt fixed HOI queries for all testing
images, which is vulnerable to the location change of objects in one specific
image. Accordingly, in this paper, we propose to enhance DETR's robustness by
mining hard-positive queries, which are forced to make correct predictions
using partial visual cues. First, we explicitly compose hard-positive queries
according to the ground-truth (GT) position of labeled human-object pairs for
each training image. Specifically, we shift the GT bounding boxes of each
labeled human-object pair so that the shifted boxes cover only a certain
portion of the GT ones. We encode the coordinates of the shifted boxes for each
labeled human-object pair into an HOI query. Second, we implicitly construct
another set of hard-positive queries by masking the top scores in
cross-attention maps of the decoder layers. The masked attention maps then only
cover partial important cues for HOI predictions. Finally, an alternate
strategy is proposed that efficiently combines both types of hard queries. In
each iteration, both DETR's learnable queries and one selected type of
hard-positive queries are adopted for loss computation. Experimental results
show that our proposed approach can be widely applied to existing DETR-based
HOI detectors. Moreover, we consistently achieve state-of-the-art performance
on three benchmarks: HICO-DET, V-COCO, and HOI-A. Code is available at
https://github.com/MuchHair/HQM.Comment: Accepted by ECCV202
A^2Net: Adjacent Aggregation Networks for Image Raindrop Removal
Existing methods for single images raindrop removal either have poor
robustness or suffer from parameter burdens. In this paper, we propose a new
Adjacent Aggregation Network (A^2Net) with lightweight architectures to remove
raindrops from single images. Instead of directly cascading convolutional
layers, we design an adjacent aggregation architecture to better fuse features
for rich representations generation, which can lead to high quality images
reconstruction. To further simplify the learning process, we utilize a
problem-specific knowledge to force the network focus on the luminance channel
in the YUV color space instead of all RGB channels. By combining adjacent
aggregating operation with color space transformation, the proposed A^2Net can
achieve state-of-the-art performances on raindrop removal with significant
parameters reduction
High-performance cVEP-BCI under minimal calibration
The ultimate goal of brain-computer interfaces (BCIs) based on visual
modulation paradigms is to achieve high-speed performance without the burden of
extensive calibration. Code-modulated visual evoked potential-based BCIs
(cVEP-BCIs) modulated by broadband white noise (WN) offer various advantages,
including increased communication speed, expanded encoding target capabilities,
and enhanced coding flexibility. However, the complexity of the
spatial-temporal patterns under broadband stimuli necessitates extensive
calibration for effective target identification in cVEP-BCIs. Consequently, the
information transfer rate (ITR) of cVEP-BCI under limited calibration usually
stays around 100 bits per minute (bpm), significantly lagging behind
state-of-the-art steady-state visual evoked potential-based BCIs (SSVEP-BCIs),
which achieve rates above 200 bpm. To enhance the performance of cVEP-BCIs with
minimal calibration, we devised an efficient calibration stage involving a
brief single-target flickering, lasting less than a minute, to extract
generalizable spatial-temporal patterns. Leveraging the calibration data, we
developed two complementary methods to construct cVEP temporal patterns: the
linear modeling method based on the stimulus sequence and the transfer learning
techniques using cross-subject data. As a result, we achieved the highest ITR
of 250 bpm under a minute of calibration, which has been shown to be comparable
to the state-of-the-art SSVEP paradigms. In summary, our work significantly
improved the cVEP performance under few-shot learning, which is expected to
expand the practicality and usability of cVEP-BCIs.Comment: 35 pages, 5 figure
Preparation of a nano emodin transfersome and study on its anti-obesity mechanism in adipose tissue of diet-induced obese rats
OBJECTIVE: To describe the preparation of nano emodin transfersome (NET) and investigate its effect on mRNA expression of adipose triglyceride lipase (ATGL) and G0/G1 switch gene 2 (G0S2) in adipose tissue of diet-induced obese rats. METHODS: NET was prepared by film-ultrasonic dispersion method. The effects of emodin components at different ratios on encapsulation efficiency were investigated.The NET envelopment rate was determined by ultraviolet spectrophotometry. The particle size and Zeta potential of NET were evaluated by Zetasizer analyzer. Sixty male SD rats were assigned to groups randomly. After 8-week treatment, body weight, wet weight of visceral fat and the percentage of body fat (PBF) were measured. Fasting blood glucose and serum lipid levels were determined. The adipose tissue section was HE stained, and the cellular diameter and quantity of adipocytes were evaluated by light microscopy. The mRNA expression of ATGL and G0S2 from the peri-renal fat tissue was assayed by RT-PCR. RESULTS: The appropriate formulation was deoxycholic acid sodium salt vs. phospholipids 1:8, cholesterol vs. phospholipids 1:3, vitamin Evs. phospholipids 1:20, and emodin vs. phospholipid 1:6. Zeta potential was −15.11 mV, and the particle size was 292.2 nm. The mean encapsulation efficiency was (69.35 ± 0.25)%. Compared with the obese model group, body weight, wet weight of visceral fat, PBF and mRNA expression of G0S2 from peri-renal fat tissue were decreased significantly after NET treatment (all P < 0.05), while high-density lipoprotein cholesterol (HDL-C), the diameter of adipocytes and mRNA expression of ATGL from peri-renal fat tissue were increased significantly (all P < 0.05). CONCLUSION: The preparation method is simple and reasonable. NET with negative electricity was small and uniform in particle size, with high encapsulation efficiency and stability. NET could reduce body weight and adipocyte size, and this effect was associated with the up-regulation of ATGL, down-regulation of G0S2 expression in the adipose tissue, and improved insulin sensitivity
Nonlinear Vibrations of Carbon Nanotubes with Thermal-Electro-Mechanical Coupling
Carbon nanotubes (CNTs) have wide-ranging applications due to their excellent mechanical and electrical properties. However, there is little research on the nonlinear mechanical properties of thermal-electro-mechanical coupling. In this paper, we study the nonlinear vibrations of CNTs by a thermal-electro-mechanical coupling beam theory. The Galerkin method is used to discretize the partial differential equation and obtain two nonlinear ordinary differential equations that describe the first- and second-order mode vibrations. Then, we obtain the approximate analytical solutions of the two equations for the primary resonance and the subharmonic resonance using the multi-scale method. The results indicate the following three points. Firstly, the temperature and electric fields have a significant influence on the first-mode vibration, while they have little influence on the second-mode vibration. Under the primary resonance, when the load amplitude of the second mode is 20 times that of the first mode, the maximal vibrational amplitude of the second is only one-fifth of the first. Under the subharmonic resonance, it is more difficult to excite the subharmonic vibration at the second-order mode than that of the first mode for the same parameters. Secondly, because the coefficient of electrical expansion (CEE) is much bigger than the coefficient of thermal expansion (CTE), CNTs are more sensitive to changes in the electric field than the temperature field. Finally, under the primary resonance, there are two bifurcation points in the frequency response curves and the load-amplitude curves. As a result, they will induce the jump phenomenon of vibrational amplitude. When the subharmonic vibration is excited, the free vibration term does not disappear, and the steady-state vibration includes two compositions
Nonlinear Vibrations of Carbon Nanotubes with Thermal-Electro-Mechanical Coupling
Carbon nanotubes (CNTs) have wide-ranging applications due to their excellent mechanical and electrical properties. However, there is little research on the nonlinear mechanical properties of thermal-electro-mechanical coupling. In this paper, we study the nonlinear vibrations of CNTs by a thermal-electro-mechanical coupling beam theory. The Galerkin method is used to discretize the partial differential equation and obtain two nonlinear ordinary differential equations that describe the first- and second-order mode vibrations. Then, we obtain the approximate analytical solutions of the two equations for the primary resonance and the subharmonic resonance using the multi-scale method. The results indicate the following three points. Firstly, the temperature and electric fields have a significant influence on the first-mode vibration, while they have little influence on the second-mode vibration. Under the primary resonance, when the load amplitude of the second mode is 20 times that of the first mode, the maximal vibrational amplitude of the second is only one-fifth of the first. Under the subharmonic resonance, it is more difficult to excite the subharmonic vibration at the second-order mode than that of the first mode for the same parameters. Secondly, because the coefficient of electrical expansion (CEE) is much bigger than the coefficient of thermal expansion (CTE), CNTs are more sensitive to changes in the electric field than the temperature field. Finally, under the primary resonance, there are two bifurcation points in the frequency response curves and the load-amplitude curves. As a result, they will induce the jump phenomenon of vibrational amplitude. When the subharmonic vibration is excited, the free vibration term does not disappear, and the steady-state vibration includes two compositions