作者: 財產(chǎn) 時間: 2025-3-21 23:19 作者: GEN 時間: 2025-3-22 01:16
Frank H. Mader,Frank Wei?gerbernced transform, encoding, reduction, and augment operations to represent candidate proxies. Then, we employ?an evolutionary algorithm to perform crossover and mutation on superior candidates within the population based on correlation evaluation. Finally, we perform generator search without training 作者: 鞭打 時間: 2025-3-22 08:04
https://doi.org/10.1007/978-3-662-54347-4sent the proxy?with computation graphs and construct the proxy search space?using instinct and interaction statistics as inputs. To identify promising proxies, our search space incorporates various types?of basic transformations and network distance operators inspired?by previous proxy and KD-loss d作者: Ascribe 時間: 2025-3-22 12:26
Beschwerden und Erkrankungen der Haut) using the trained reconstruction and diffusion models, and (3) an innovative application of SDS for finalizing PBR generation while keeping a fixed albedo based on Stable Diffusion model. Extensive evaluations demonstrate that UniDream surpasses existing methods in generating 3D objects with clear作者: occult 時間: 2025-3-22 16:03 作者: occult 時間: 2025-3-22 20:26
https://doi.org/10.1007/978-3-030-37258-3-Occ, a novel method that encodes occupancy data into a compact latent feature space using a VQ-VAE. This approach simplifies semantic occupancy prediction into feature simulation in the VQ latent space, making it easier and more memory-efficient. Our method enables direct generation of semantic occ作者: 辯論的終結 時間: 2025-3-23 00:12
https://doi.org/10.1007/978-3-030-37258-3 the ray-based kernel and employ an optimized sparse kernel to gather the input rays efficiently and render the optimized rays with our layered DoF volume rendering. We synthesize a dataset with defocused dynamic scenes for our task, and extensive experiments on our dataset show that our method outp作者: epicondylitis 時間: 2025-3-23 01:29 作者: 能得到 時間: 2025-3-23 07:57 作者: Spartan 時間: 2025-3-23 10:36 作者: Ossification 時間: 2025-3-23 15:24
Developing Academic Women Leaders in STEM The CCM employs an entropy-based ensembling strategy to encourage the model to learn from both the consistent and conflicting predictions between the teachers. Experimental results demonstrate the effectiveness and superiority of AD-MT on the 2D and 3D medical segmentation benchmarks across various作者: 紀念 時間: 2025-3-23 20:07 作者: Common-Migraine 時間: 2025-3-24 01:10 作者: intoxicate 時間: 2025-3-24 04:01 作者: Stricture 時間: 2025-3-24 08:57
Kathryn Backet-Milburn,Lindsay MacHardymultimodality fusion module, and a negative pair discriminator. These components enhance the model’s ability to handle disturbances in informative tokens and prioritize relational elements during image generation ..作者: Licentious 時間: 2025-3-24 10:40 作者: instate 時間: 2025-3-24 16:03 作者: 不愛防注射 時間: 2025-3-24 21:06
,Auto-GAS: Automated Proxy Discovery for?Training-Free Generative Architecture Search,nced transform, encoding, reduction, and augment operations to represent candidate proxies. Then, we employ?an evolutionary algorithm to perform crossover and mutation on superior candidates within the population based on correlation evaluation. Finally, we perform generator search without training 作者: 騷擾 時間: 2025-3-25 01:08 作者: 分發(fā) 時間: 2025-3-25 04:44 作者: 起皺紋 時間: 2025-3-25 10:11 作者: 強行引入 時間: 2025-3-25 12:46
,nuCraft: Crafting High Resolution 3D Semantic Occupancy for?Unified 3D Scene Understanding,-Occ, a novel method that encodes occupancy data into a compact latent feature space using a VQ-VAE. This approach simplifies semantic occupancy prediction into feature simulation in the VQ latent space, making it easier and more memory-efficient. Our method enables direct generation of semantic occ作者: 新娘 時間: 2025-3-25 18:23 作者: 火光在搖曳 時間: 2025-3-25 22:48
,PiTe: Pixel-Temporal Alignment for?Large Video-Language Model,multi-modal pre-training dataset PiTe-143k, the dataset provision of moving trajectories in pixel level for all individual objects, that appear and mention in the video and caption both, by our automatic annotation pipeline. Meanwhile, . demonstrates astounding capabilities on myriad video-related m作者: Expediency 時間: 2025-3-26 01:01 作者: Gastric 時間: 2025-3-26 05:49
,FreeDiff: Progressive Frequency Truncation for?Image Editing with?Diffusion Models,ency signals for editing. Leveraging this insight, we introduce a novel fine-tuning free approach that employs progressive .qu.ncy truncation to refine the guidance of .usion models for universal editing tasks (.). Our method achieves comparable results with state-of-the-art methods across a variety作者: 能量守恒 時間: 2025-3-26 09:46 作者: 小卒 時間: 2025-3-26 13:54 作者: 固執(zhí)點好 時間: 2025-3-26 18:53
Text-Guided Video Masked Autoencoder,tion, we next introduce a unified framework for joint MAE and masked video-text contrastive learning. We show that across existing masking algorithms, unifying MAE and masked video-text contrastive learning improves downstream performance compared to pure MAE on a variety of video recognition tasks,作者: 流眼淚 時間: 2025-3-26 23:45
,Diffusion Models for?Open-Vocabulary Segmentation,elies solely on pre-trained components and outputs the synthesised segmenter directly, without training. Our approach shows strong performance on a range of benchmarks, obtaining a lead of more than 5% over prior work on PASCAL VOC.作者: vascular 時間: 2025-3-27 02:20 作者: Ingenuity 時間: 2025-3-27 05:18 作者: 捏造 時間: 2025-3-27 11:15 作者: nuclear-tests 時間: 2025-3-27 15:53
Developing Academic Women Leaders in STEM of 51.9 on COCO, matching the current state-of-the-art detectors. We conduct extensive experiments on 13 downstream datasets and Plain-Det demonstrates strong generalization capability. Code is release at ..作者: Foment 時間: 2025-3-27 20:57
Plain-Det: A Plain Multi-dataset Object Detector, of 51.9 on COCO, matching the current state-of-the-art detectors. We conduct extensive experiments on 13 downstream datasets and Plain-Det demonstrates strong generalization capability. Code is release at ..作者: 詞匯記憶方法 時間: 2025-3-27 23:15
Alliances for Sustainable Developmenthing problems. The intuition of synchronous diffusion is that diffusing the same input function on two different shapes results in consistent outputs. Using different challenging datasets, we demonstrate that our novel regularisation can substantially improve the state-of-the-art in shape matching, especially in the presence of topological noise.作者: 啪心兒跳動 時間: 2025-3-28 02:54 作者: 得體 時間: 2025-3-28 08:08 作者: 典型 時間: 2025-3-28 14:20 作者: hair-bulb 時間: 2025-3-28 14:47
,Synchronous Diffusion for?Unsupervised Smooth Non-rigid 3D Shape Matching,hing problems. The intuition of synchronous diffusion is that diffusing the same input function on two different shapes results in consistent outputs. Using different challenging datasets, we demonstrate that our novel regularisation can substantially improve the state-of-the-art in shape matching, especially in the presence of topological noise.作者: expound 時間: 2025-3-28 19:45 作者: 全等 時間: 2025-3-28 23:48
,SignAvatars: A Large-Scale 3D Sign Language Holistic Motion Dataset and?Benchmark, hard-of-hearing individuals. While there has been an exponentially growing number of research regarding digital communication, the majority of existing communication technologies primarily cater to spoken or written languages, instead of SL, the essential communication method for Deaf and hard-of-h作者: LUDE 時間: 2025-3-29 04:35 作者: 歌唱隊 時間: 2025-3-29 09:25
,Auto-GAS: Automated Proxy Discovery for?Training-Free Generative Architecture Search,rative models like Generative Adversarial Networks (GANs) are now widely used in many real-time applications. Previous GAS methods use differentiable?or evolutionary search to find optimal GAN generators for?fast inference and memory efficiency. However, the high computational overhead of these trai作者: Fsh238 時間: 2025-3-29 13:47 作者: 含糊 時間: 2025-3-29 16:05 作者: notice 時間: 2025-3-29 20:26
,:?Navigate Weakly-Supervised Temporal Grounded Video Question Answering via?Bi-directional Reasonin content from temporal and causal perspectives. Traditional supervised VQA methods gain this capability through meticulously annotated QA datasets, while advanced visual-language models exhibit remarkable performance due to large-scale visual-text pretraining data. Nevertheless, due to potential lan作者: ARC 時間: 2025-3-30 00:08
,Spectral Subsurface Scattering for?Material Classification,nts have individually been used in material classification, we argue that the strong spectral dependence of subsurface scattering lends itself to highly discriminative features. However, obtaining . measurements requires a time-consuming hyperspectral scan. We avoid this by showing that a carefully 作者: Spartan 時間: 2025-3-30 06:52 作者: foppish 時間: 2025-3-30 11:16 作者: 幻影 時間: 2025-3-30 13:08 作者: 正式演說 時間: 2025-3-30 19:16
,CarFormer: Self-driving with?Learned Object-Centric Representations,. In this paper, we propose to learn object-centric representations in BEV to distill a complex scene into more actionable information for self-driving. We first learn to place objects into slots with a slot attention model on BEV sequences. Based on these object-centric representations, we then tra作者: 露天歷史劇 時間: 2025-3-30 21:17 作者: 群居動物 時間: 2025-3-31 01:29 作者: Cardiac 時間: 2025-3-31 06:14 作者: 搜集 時間: 2025-3-31 09:47 作者: vascular 時間: 2025-3-31 15:36
,Synchronous Diffusion for?Unsupervised Smooth Non-rigid 3D Shape Matching, Nevertheless, respective methods struggle to obtain spatially smooth pointwise correspondences due to the lack of proper regularisation. In this work, inspired by the success of message passing on graphs, we propose a . which we use as regularisation to achieve smoothness in non-rigid 3D shape matc作者: 靦腆 時間: 2025-3-31 18:20
