133 research outputs found

    Revisiting the Parameter Efficiency of Adapters from the Perspective of Precision Redundancy

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    Current state-of-the-art results in computer vision depend in part on fine-tuning large pre-trained vision models. However, with the exponential growth of model sizes, the conventional full fine-tuning, which needs to store a individual network copy for each tasks, leads to increasingly huge storage and transmission overhead. Adapter-based Parameter-Efficient Tuning (PET) methods address this challenge by tuning lightweight adapters inserted into the frozen pre-trained models. In this paper, we investigate how to make adapters even more efficient, reaching a new minimum size required to store a task-specific fine-tuned network. Inspired by the observation that the parameters of adapters converge at flat local minima, we find that adapters are resistant to noise in parameter space, which means they are also resistant to low numerical precision. To train low-precision adapters, we propose a computational-efficient quantization method which minimizes the quantization error. Through extensive experiments, we find that low-precision adapters exhibit minimal performance degradation, and even 1-bit precision is sufficient for adapters. The experimental results demonstrate that 1-bit adapters outperform all other PET methods on both the VTAB-1K benchmark and few-shot FGVC tasks, while requiring the smallest storage size. Our findings show, for the first time, the significant potential of quantization techniques in PET, providing a general solution to enhance the parameter efficiency of adapter-based PET methods. Code: https://github.com/JieShibo/PETL-ViTComment: Accepted to ICCV 202

    Restoration of horizontal stability in complete acromioclavicular joint separations: surgical technique and preliminary results

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    BACKGROUND: Our purpose was to investigate the clinical efficacy of arthroscope-assisted acromioclavicular ligament reconstruction in combination with double endobutton coracoclavicular ligament reconstruction for the treatment of complete acromioclavicular joint dislocation. METHODS: During the period from February 2010 to October 2012, ten patients with Rockwood types IV and V acromioclavicular joint dislocation were hospitalized and nine were treated with acromioclavicular ligament reconstruction combined with double endobutton of coracoclavicular ligament reconstruction. The improvement in shoulder functions was assessed using a Constant score and visual analog scale (VAS) system. RESULTS: The mean follow-up period was 33.6 ± 5.4 months. The mean Constant scores improved from 25.2 ± 6.6 preoperatively to 92.4 ± 6.5 postoperatively, while the mean VAS score decreased from 5.9 ± 1.4 to 1.2 ± 0.9; significant differences were observed. The final follow-up revealed that excellent outcomes were achieved in eight patients and good outcome in two patients. CONCLUSION: Arthroscope-assisted acromioclavicular ligament reconstruction in combination with double endobutton of coracoclavicular ligament reconstruction is an effective approach for treatment of acute complete acromioclavicular joint dislocation

    ILNet: Low-level Matters for Salient Infrared Small Target Detection

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    Infrared small target detection is a technique for finding small targets from infrared clutter background. Due to the dearth of high-level semantic information, small infrared target features are weakened in the deep layers of the CNN, which underachieves the CNN's representation ability. To address the above problem, in this paper, we propose an infrared low-level network (ILNet) that considers infrared small targets as salient areas with little semantic information. Unlike other SOTA methods, ILNet pays greater attention to low-level information instead of treating them equally. A new lightweight feature fusion module, named Interactive Polarized Orthogonal Fusion module (IPOF), is proposed, which integrates more important low-level features from the shallow layers into the deep layers. A Dynamic One-Dimensional Aggregation layers (DODA) are inserted into the IPOF, to dynamically adjust the aggregation of low dimensional information according to the number of input channels. In addition, the idea of ensemble learning is used to design a Representative Block (RB) to dynamically allocate weights for shallow and deep layers. Experimental results on the challenging NUAA-SIRST (78.22% nIoU and 1.33e-6 Fa) and IRSTD-1K (68.91% nIoU and 3.23e-6 Fa) dataset demonstrate that the proposed ILNet can get better performances than other SOTA methods. Moreover, ILNet can obtain a greater improvement with the increasement of data volume. Training code are available at https://github.com/Li-Haoqing/ILNet

    Click on Mask: A Labor-efficient Annotation Framework with Level Set for Infrared Small Target Detection

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    Infrared Small Target Detection is a challenging task to separate small targets from infrared clutter background. Recently, deep learning paradigms have achieved promising results. However, these data-driven methods need plenty of manual annotation. Due to the small size of infrared targets, manual annotation consumes more resources and restricts the development of this field. This letter proposed a labor-efficient and cursory annotation framework with level set, which obtains a high-quality pseudo mask with only one cursory click. A variational level set formulation with an expectation difference energy functional is designed, in which the zero level contour is intrinsically maintained during the level set evolution. It solves the issue that zero level contour disappearing due to small target size and excessive regularization. Experiments on the NUAA-SIRST and IRSTD-1k datasets reveal that our approach achieves superior performance. Code is available at https://github.com/Li-Haoqing/COM.Comment: 4 pages, 5 figures, references adde

    Asymmetric opening of HIV-1 Env bound to CD4 and a coreceptor-mimicking antibody

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    The human immunodeficiency virus (HIV-1) envelope (Env) glycoprotein, a (gp120–gp41)₃ trimer, mediates fusion of viral and host cell membranes after gp120 binding to host receptor CD4. Receptor binding triggers conformational changes allowing coreceptor (CCR5) recognition through CCR5’s tyrosine-sulfated amino (N) terminus, release of the gp41 fusion peptide and fusion. We present 3.3 Å and 3.5 Å cryo-EM structures of E51, a tyrosine-sulfated coreceptor-mimicking antibody, complexed with a CD4-bound open HIV-1 native-like Env trimer. Two classes of asymmetric Env interact with E51, revealing tyrosine-sulfated interactions with gp120 mimicking CCR5 interactions, and two conformations of gp120–gp41 protomers (A and B protomers in AAB and ABB trimers) that differ in their degree of CD4-induced trimer opening and induction of changes to the fusion peptide. By integrating the new structural information with previous closed and open envelope trimer structures, we modeled the order of conformational changes on the path to coreceptor binding site exposure and subsequent viral–host cell membrane fusion

    X-ray and EM structures of a natively glycosylated HIV-1 envelope trimer

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    The structural and biochemical characterization of broadly neutralizing anti-HIV-1 antibodies (bNAbs) has been essential in guiding the design of potential vaccines to prevent infection by HIV-1. While these studies have revealed critical mechanisms by which bNAbs recognize and/or accommodate N-glycans on the trimeric envelope glycoprotein (Env), they have been limited to the visualization of high-mannose glycan forms only, since heterogeneity introduced from the presence of complex glycans makes it difficult to obtain high-resolution structures. 3.5 and 3.9 Å resolution crystal structures of the HIV-1 Env trimer with fully processed and native glycosylation were solved, revealing a glycan shield of high-mannose and complex-type N-glycans that were used to define the complete epitopes of two bNAbs. Here, the refinement of the N-glycans in the crystal structures is discussed and comparisons are made with glycan densities in glycosylated Env structures derived by single-particle cryo-electron microscopy

    X-ray and EM structures of a natively glycosylated HIV-1 envelope trimer

    Get PDF
    The structural and biochemical characterization of broadly neutralizing anti-HIV-1 antibodies (bNAbs) has been essential in guiding the design of potential vaccines to prevent infection by HIV-1. While these studies have revealed critical mechanisms by which bNAbs recognize and/or accommodate N-glycans on the trimeric envelope glycoprotein (Env), they have been limited to the visualization of high-mannose glycan forms only, since heterogeneity introduced from the presence of complex glycans makes it difficult to obtain high-resolution structures. 3.5 and 3.9 Å resolution crystal structures of the HIV-1 Env trimer with fully processed and native glycosylation were solved, revealing a glycan shield of high-mannose and complex-type N-glycans that were used to define the complete epitopes of two bNAbs. Here, the refinement of the N-glycans in the crystal structures is discussed and comparisons are made with glycan densities in glycosylated Env structures derived by single-particle cryo-electron microscopy
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