作者: extract 時(shí)間: 2025-3-22 00:09 作者: 安撫 時(shí)間: 2025-3-22 03:20
Cinthia Pestana Haddad,Kai Lehmann are inevitably biased to object classes of limited pairwise patterns, leading to poor generalization to rare or unseen object combinations. Therefore, we are interested in learning object-agnostic visual features for more generalizable relationship models. By “agnostic”, we mean that the feature is作者: MUTED 時(shí)間: 2025-3-22 07:47 作者: finale 時(shí)間: 2025-3-22 11:56 作者: 粗鄙的人 時(shí)間: 2025-3-22 13:27
Palgrave Studies in European Union Politicsthey predict if the underlying factors have changed? Interestingly, in most cases humans can predict the effects of similar collisions with different conditions such as changes in mass, friction, etc. It is postulated this is primarily because we learn to model physics with meaningful latent variabl作者: 粗鄙的人 時(shí)間: 2025-3-22 18:45
Introduction: A Crisis Decade for the EU,al activity analysis, deception detection, etc. We address subtle expression recognition through convolutional neural networks (CNNs) by developing multi-task learning (MTL) methods to effectively leverage a side task: facial landmark detection. Existing MTL methods follow a design pattern of shared作者: 向下五度才偏 時(shí)間: 2025-3-23 00:53
Introduction: A Crisis Decade for the EU, costly. By combining the advantages of 3D scanning, reasoning, and GAN-based domain adaptation techniques, we introduce a novel pipeline named SRDA to obtain large quantities of training samples with very minor effort. Our pipeline is well-suited to scenes that can be scanned, i.e. most indoor and 作者: 極大痛苦 時(shí)間: 2025-3-23 02:06
Alain Guggenbühl,Margareta Theelen Our key idea is to utilize the fact that predictions from different views of the same or similar objects should be consistent with each other. Such view consistency can provide effective regularization for keypoint prediction on unlabeled instances. In addition, we introduce a geometric alignment t作者: 執(zhí)拗 時(shí)間: 2025-3-23 09:35 作者: 斥責(zé) 時(shí)間: 2025-3-23 09:50 作者: hegemony 時(shí)間: 2025-3-23 16:28
Alain Guggenbühl,Margareta Theelenlier layers for consumption by deeper layers. Such aggregation is critical to facilitate training of very deep networks in an end-to-end manner. This is a primary reason for the widespread adoption of residual networks, which aggregate outputs via cumulative summation. While subsequent works investi作者: 撫慰 時(shí)間: 2025-3-23 21:29
Alain Guggenbühl,Margareta Theelenntly based on the inverted multi-index, the recently proposed generalization of the inverted index structure. The multi-index provides a very fine-grained partition of the feature space that allows extracting concise and accurate short-lists of candidates for the search queries..In this paper, we ar作者: DOLT 時(shí)間: 2025-3-24 00:04
Anniek de Ruijter,Tamara K. Herveyy of individual units by finding meaningful images that maximize their activation. However, comparably little attention has been paid to visualizing to what image transformations units in DNNs are invariant. Here we propose a method to discover invariances in the responses of hidden layer units of d作者: Exclaim 時(shí)間: 2025-3-24 02:46
Pensions and the Lisbon Strategy,rease in overall performance when training with new classes added incrementally. This is due to current neural network architectures requiring the entire dataset, consisting of all the samples from the old as well as the new classes, to update the model—a requirement that becomes easily unsustainabl作者: 處理 時(shí)間: 2025-3-24 08:39 作者: Jargon 時(shí)間: 2025-3-24 13:03
https://doi.org/10.1007/978-3-319-65792-9-and-Bound (BnB) search paradigm to maximize the consensus of the polynomials. These polynomials are parameterized by the entries of, either the Dual Image of Absolute Conic (DIAC) or the Plane-at-Infinity (PaI). During the BnB search, we exploit the theory of sampling algebraic varieties, to test t作者: Ingredient 時(shí)間: 2025-3-24 16:53 作者: liposuction 時(shí)間: 2025-3-24 21:43
https://doi.org/10.1007/978-3-030-01258-83D; artificial intelligence; computer vision; image processing; image reconstruction; image segmentation; 作者: Lasting 時(shí)間: 2025-3-25 01:46 作者: Cognizance 時(shí)間: 2025-3-25 03:39
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234198.jpg作者: 遺留之物 時(shí)間: 2025-3-25 10:27
Computer Vision – ECCV 2018978-3-030-01258-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: CHANT 時(shí)間: 2025-3-25 14:47 作者: 時(shí)間等 時(shí)間: 2025-3-25 16:29 作者: 禁止,切斷 時(shí)間: 2025-3-25 20:44 作者: 不自然 時(shí)間: 2025-3-26 04:08
Sparsely Aggregated Convolutional Networksmonstrate this simple design change offers superior performance with fewer parameters and lower computational requirements. Moreover, we show that sparse aggregation allows networks to scale more robustly to 1000+ layers, thereby opening future avenues for training long-running visual processes.作者: Definitive 時(shí)間: 2025-3-26 05:11 作者: Allege 時(shí)間: 2025-3-26 09:36 作者: FIR 時(shí)間: 2025-3-26 13:26
Cinthia Pestana Haddad,Kai Lehmannll on block towers and tools in both synthetic and real scenarios; we also demonstrate that visual and physical observations often provide complementary signals. We further present ablation and behavioral studies to better understand our model and contrast it with human performance.作者: Ceramic 時(shí)間: 2025-3-26 17:34 作者: 消瘦 時(shí)間: 2025-3-26 23:38 作者: adipose-tissue 時(shí)間: 2025-3-27 03:31
Alain Guggenbühl,Margareta Theelenes its good qualities to its encoder and decoder, which are designed following concepts from systems identification theory and exploit the dynamics-based invariants of the data. Extensive experiments using several standard video datasets show that DYAN is superior generating frames and that it generalizes well across domains.作者: Coronary 時(shí)間: 2025-3-27 07:48
Education and the Lisbon Strategy,nsive experiments verify the effectiveness of our approach across three phrase grounding datasets, Flickr30K Entities, ReferIt Game, and Visual Genome, where we obtain a (resp.) 4%, 3%, and 4% improvement in grounding performance over a strong region-phrase embedding baseline (Code: .).作者: 出來 時(shí)間: 2025-3-27 11:06
Physical Primitive Decompositionll on block towers and tools in both synthetic and real scenarios; we also demonstrate that visual and physical observations often provide complementary signals. We further present ablation and behavioral studies to better understand our model and contrast it with human performance.作者: Observe 時(shí)間: 2025-3-27 16:17
Combining 3D Model Contour Energy and Keypoints for Object Trackingse estimation. Owing to its combined nature, our method eliminates numerous issues of keypoint-based and edge-based approaches. We demonstrate the efficiency of our method by comparing it with state-of-the-art methods on a public benchmark dataset that includes videos with various lighting conditions, movement patterns, and speed.作者: 一再遛 時(shí)間: 2025-3-27 19:51 作者: scrutiny 時(shí)間: 2025-3-28 00:54
DYAN: A Dynamical Atoms-Based Network for Video Predictiones its good qualities to its encoder and decoder, which are designed following concepts from systems identification theory and exploit the dynamics-based invariants of the data. Extensive experiments using several standard video datasets show that DYAN is superior generating frames and that it generalizes well across domains.作者: coagulation 時(shí)間: 2025-3-28 03:06
Conditional Image-Text Embedding Networksnsive experiments verify the effectiveness of our approach across three phrase grounding datasets, Flickr30K Entities, ReferIt Game, and Visual Genome, where we obtain a (resp.) 4%, 3%, and 4% improvement in grounding performance over a strong region-phrase embedding baseline (Code: .).作者: LVAD360 時(shí)間: 2025-3-28 09:19
SRDA: Generating Instance Segmentation Annotation via Scanning, Reasoning and Domain Adaptationsome outdoor scenarios. To evaluate our performance, we build three representative scenes and a new dataset, with 3D models of various common objects categories and annotated real-world scene images. Extensive experiments show that our pipeline can achieve decent instance segmentation performance given very low human labor cost.作者: 北極人 時(shí)間: 2025-3-28 13:10
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistencyerm to regularize predictions in the target domain. The resulting loss function can be effectively optimized via alternating minimization. We demonstrate the effectiveness of our approach on real datasets and present experimental results showing that our approach is superior to state-of-the-art general-purpose domain adaptation techniques.作者: Multiple 時(shí)間: 2025-3-28 17:36
Conference proceedings 2018The papers are organized in topical?sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization;?matching and recognition; video attention; and poster sessions..作者: CLOT 時(shí)間: 2025-3-28 20:57
0302-9743 missions. The papers are organized in topical?sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization;?matching and recognition; video attention; and poster sessions..978-3-030-01257-1978-3-030-01258-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Countermand 時(shí)間: 2025-3-29 01:37
Introduction: A Crisis Decade for the EU,some outdoor scenarios. To evaluate our performance, we build three representative scenes and a new dataset, with 3D models of various common objects categories and annotated real-world scene images. Extensive experiments show that our pipeline can achieve decent instance segmentation performance given very low human labor cost.作者: Nonconformist 時(shí)間: 2025-3-29 06:14 作者: 輪流 時(shí)間: 2025-3-29 09:39
Conference proceedings 2018, ECCV 2018, held in Munich, Germany, in September 2018..The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical?sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstructi作者: CURT 時(shí)間: 2025-3-29 14:42 作者: Offstage 時(shí)間: 2025-3-29 17:28
Cinthia Pestana Haddad,Kai Lehmannttention module on tensor to select the most discriminative reasoning process for inference. Third, we optimize the proposed DA-NTN by learning a label regression with KL-divergence losses. Such a design enables scalable training and fast convergence over a large number of answer set. We integrate t作者: 驚奇 時(shí)間: 2025-3-29 19:46
Cinthia Pestana Haddad,Kai Lehmannic visual patterns. Extensive experiments on two visual relationship benchmarks show that by using our pre-trained features, naive relationship models can be consistently improved and even outperform other state-of-the-art relationship models. Code has been made available at: ..作者: Hay-Fever 時(shí)間: 2025-3-30 01:50 作者: 使害怕 時(shí)間: 2025-3-30 04:31
Introduction: A Crisis Decade for the EU,datasets without suffering from dataset distribution shift. To advance subtle expression recognition, we contribute a Large-scale Subtle Emotions and Mental States in the Wild?database (LSEMSW). LSEMSW?includes a variety of cognitive states as well as basic emotions. It contains 176K images, manuall作者: 皮薩 時(shí)間: 2025-3-30 09:22
Alain Guggenbühl,Margareta Theeleno apply the Gradient Estimation attacks successfully against real-world classifiers hosted by Clarifai. Further, we evaluate black-box attacks against state-of-the-art defenses based on adversarial training and show that the Gradient Estimation attacks are very effective even against these defenses.作者: 頂點(diǎn) 時(shí)間: 2025-3-30 16:19
Anniek de Ruijter,Tamara K. Herveyifferences with ResNet-50 in its corresponding layers. We conclude that invariance transformations are a major computational component learned by DNNs and we provide a systematic method to study them.作者: Incise 時(shí)間: 2025-3-30 18:16 作者: 懶惰人民 時(shí)間: 2025-3-30 20:52
European Security Community Expansion,ector and by incorporating a face verification network, the attribute-guided network becomes the . which produces high-quality and interesting results on identity transfer. We demonstrate three applications on identity-guided conditional CycleGAN: identity-preserving face superresolution, face swapp作者: Flagging 時(shí)間: 2025-3-31 04:04
Deep Attention Neural Tensor Network for Visual Question Answeringttention module on tensor to select the most discriminative reasoning process for inference. Third, we optimize the proposed DA-NTN by learning a label regression with KL-divergence losses. Such a design enables scalable training and fast convergence over a large number of answer set. We integrate t作者: venous-leak 時(shí)間: 2025-3-31 07:13 作者: 輕信 時(shí)間: 2025-3-31 11:49
Interpretable Intuitive Physics Model(cube, cone, cylinder, spheres etc.) and test on collisions of unseen combinations of shapes. Furthermore, we demonstrate our model generalizes well even when similar scenes are simulated with different underlying properties.作者: 草率男 時(shí)間: 2025-3-31 17:04
Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental Statesdatasets without suffering from dataset distribution shift. To advance subtle expression recognition, we contribute a Large-scale Subtle Emotions and Mental States in the Wild?database (LSEMSW). LSEMSW?includes a variety of cognitive states as well as basic emotions. It contains 176K images, manuall作者: Euthyroid 時(shí)間: 2025-3-31 19:59 作者: 名字的誤用 時(shí)間: 2025-3-31 23:35 作者: 上腭 時(shí)間: 2025-4-1 04:40 作者: Vsd168 時(shí)間: 2025-4-1 08:48
