作者: 雜色 時間: 2025-3-21 21:48
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/242310.jpg作者: 弄臟 時間: 2025-3-22 04:27
https://doi.org/10.1007/978-3-031-72624-8artificial intelligence; computer networks; computer systems; computer vision; education; Human-Computer 作者: RAG 時間: 2025-3-22 05:54 作者: ASSET 時間: 2025-3-22 12:17 作者: Inflated 時間: 2025-3-22 16:25
Allgemeinchirurgische Operationensks. However, the broader application of spectral sensors in mobile photography is hindered by the inherent complexity of spectral images and the constraints of spectral imaging capabilities. To overcome these challenges, we propose a joint RGB-Spectral decomposition model guided enhancement framewo作者: Inflated 時間: 2025-3-22 19:43
Allgemeinchirurgische Operationenion and incorporate spatial information through additional positional embedding. However, they only consider the local positional information within each image token and cannot effectively model the global spatial relations of the underlying scene. To address this challenge, we propose an efficient 作者: dictator 時間: 2025-3-23 01:01
https://doi.org/10.1007/978-3-642-68941-3ents of object boxes, which cannot capture more fine-grained scene information. In this paper, we explore a new framework of learning a world model, OccWorld, in the 3D occupancy space to simultaneously predict the movement of the ego car and the evolution of the surrounding scenes. We propose to le作者: congenial 時間: 2025-3-23 03:27
Schrittmacher und Defibrillatoren,sual content. However, these models lack an understanding of . concepts. In this work, we take a first step toward the . of VLMs, enabling them to learn and reason over user-provided concepts. For example, we explore whether these models can learn to . you in an image and . what you are doing, tailo作者: 傾聽 時間: 2025-3-23 05:50
Kommunikation an Schnittstellen,In this paper, we introduce AMEGO, a novel approach aimed at enhancing the comprehension of very-long egocentric videos. Inspired by the human’s ability to maintain information from a single watching, AMEGO focuses on constructing a self-contained representations from one egocentric video, capturing作者: Biguanides 時間: 2025-3-23 11:34 作者: 軌道 時間: 2025-3-23 15:38 作者: 鉆孔 時間: 2025-3-23 20:37
Schrittmacher und Defibrillatoren,. To tackle this challenge, previous methods have utilized generative models to increase data by generating synthetic samples. However, existing methods often overlook the importance of considering the context of biological tissues (e.g., shape, spatial layout, and tissue type) Moreover, while gener作者: 流浪 時間: 2025-3-23 23:49
,Verb?nde und Boolesche Algebren,t performance while preventing privacy violations and memory overhead problems. Nonetheless, existing PCL approaches face significant computational burdens because of two Vision Transformer (ViT) feed-forward stages; one is for the query ViT that generates a prompt query to select prompts inside a p作者: Substance 時間: 2025-3-24 05:11 作者: FIR 時間: 2025-3-24 09:56 作者: Gratuitous 時間: 2025-3-24 12:06 作者: 叢林 時間: 2025-3-24 14:53 作者: 概觀 時間: 2025-3-24 22:22 作者: MUTE 時間: 2025-3-25 02:07
Die Gewinn- und Verlustrechnungure trajectories of other agents in traffic scenes, directly using them to plan for the ego vehicle is often unsatisfactory. This is due to misaligned objectives during training and deployment: a planner that only aims to imitate human driver trajectories is insufficient to accomplish driving tasks 作者: Kinetic 時間: 2025-3-25 05:57
Eigenmittel und deren Verwendungng work proposes an online point-wise clustering method with a simplified equal class-size constraint on the novel classes to avoid degenerate solutions. However, the inherent imbalanced distribution of novel classes in point clouds typically violates the equal class-size constraint. Moreover, point作者: 雜色 時間: 2025-3-25 10:32 作者: 有常識 時間: 2025-3-25 13:26
Banken, deren Sicherung und Beaufsichtigunghods that focus on warping images frame by frame, we advocate explicitly warping the intermediate latent code of the pre-trained text-to-image diffusion model for high-quality image generation and generalization ability. To further enhance the fidelity of the generated images, we also propose a feat作者: Heretical 時間: 2025-3-25 19:23
Banken, deren Sicherung und Beaufsichtigungy, respectively. Extensive experiments reveal that . significantly surpasses existing methods, delivering highly authentic scene generation with exceptional visual quality, without training or fine-tuning on datasets or reconstructing 3D point clouds in advance.作者: Coma704 時間: 2025-3-25 22:20 作者: Derogate 時間: 2025-3-26 02:15
Conference proceedings 2025uter Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024...The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinf作者: LEVY 時間: 2025-3-26 07:40 作者: 典型 時間: 2025-3-26 11:29 作者: 不透氣 時間: 2025-3-26 14:05 作者: 吵鬧 時間: 2025-3-26 18:43 作者: 松軟 時間: 2025-3-26 23:12 作者: FEIGN 時間: 2025-3-27 03:55
Schrittmacher und Defibrillatoren, output modalities, we propose to train a new PBR model that is tightly linked to a frozen RGB model using a novel cross-network communication paradigm. As the base RGB model is fully frozen, the proposed method retains its general performance and remains compatible with . IPAdapters for that base model.作者: 畸形 時間: 2025-3-27 05:33 作者: 學術討論會 時間: 2025-3-27 10:24 作者: circuit 時間: 2025-3-27 14:48 作者: Fortify 時間: 2025-3-27 19:33
,SpatialFormer: Towards Generalizable Vision Transformers with?Explicit Spatial Understanding,etter generalization, we employ a decoder-only overall architecture and propose a bilateral cross-attention block for efficient interactions between context and spatial tokens. SpatialFormer learns transferable image representations with explicit scene understanding, where the output spatial tokens 作者: URN 時間: 2025-3-28 00:57
,OccWorld: Learning a?3D Occupancy World Model for?Autonomous Driving, obtain discrete scene tokens to describe the surrounding scenes. We then adopt a GPT-like spatial-temporal generative transformer to generate subsequent scene and ego tokens to decode the future occupancy and ego trajectory. Extensive experiments on nuScenes demonstrate the ability of OccWorld to e作者: aesthetic 時間: 2025-3-28 03:36
,MyVLM: Personalizing VLMs for?User-Specific Queries,ng the language model to naturally integrate the target concept in its generated response. We apply our technique to BLIP-2 and LLaVA for personalized image captioning and further show its applicability for personalized visual question-answering. Our experiments demonstrate our ability to generalize作者: epicardium 時間: 2025-3-28 07:51
,Power Variable Projection for?Initialization-Free Large-Scale Bundle Adjustment,s state-of-the-art results in terms of speed and accuracy. To our knowledge, this work is the first to address the scalability of BA without initialization opening new venues for initialization-free structure-from-motion.作者: UNT 時間: 2025-3-28 12:14
,Co-synthesis of?Histopathology Nuclei Image-Label Pairs Using a?Context-Conditioned Joint Diffusionlated text prompts to incorporate spatial and structural context information into the generation targets. Moreover, we enhance the granularity of our synthesized semantic labels by generating instance-wise nuclei labels using distance maps synthesized concurrently in conjunction with the images and 作者: COM 時間: 2025-3-28 18:04
One-Stage Prompt-Based Continual Learning,introduce a Query-Pool Regularization (QR) loss that regulates the relationship between the prompt query and the prompt pool to improve representation power. The QR loss is only applied during training time, so there is no computational overhead at inference from the QR loss. With the QR loss, our a作者: Enliven 時間: 2025-3-28 22:16
,SpaceJAM: a?Lightweight and?Regularization-Free Method for?Fast Joint Alignment of?Images, while significantly reducing computational demands and achieving at least a 10x speedup. SpaceJAM sets a new standard for rapid and effective image alignment, making the process more accessible and efficient. Our code is available at: ..作者: 壓迫 時間: 2025-3-29 02:17 作者: avenge 時間: 2025-3-29 05:49
,: Quantization in?Low Data Regimes with?Generative Synthetic Data,ta generation process, enhancing fidelity through the inversion of learnable token embeddings. Through rigorous experimentation, . establishes new benchmarks in data-free and data-scarce quantization, significantly outperforming existing methods in accuracy and efficiency, thereby setting a new stan作者: 即席演說 時間: 2025-3-29 09:18 作者: deceive 時間: 2025-3-29 13:35 作者: 被告 時間: 2025-3-29 16:19 作者: 遍及 時間: 2025-3-29 19:45
,Dual-Level Adaptive Self-labeling for?Novel Class Discovery in?Point Cloud Segmentation,ning, reducing noise in generated segmentation. Finally, we conduct extensive experiments on two widely used datasets, SemanticKITTI and SemanticPOSS, and the results show our method outperforms the state of the art by a large margin.作者: Contort 時間: 2025-3-30 01:54
,EBDM: Exemplar-Guided Image Translation with?Brownian-Bridge Diffusion Models,image. To efficiently guide the diffusion process toward the style of exemplar, we delineate three pivotal components: the Global Encoder, the Exemplar Network, and the Exemplar Attention Module to incorporate global and detailed texture information from exemplar images. Leveraging Bridge diffusion,作者: 歡笑 時間: 2025-3-30 05:19
https://doi.org/10.1007/978-3-531-92543-1tion of important city blocks and buildings. Our approach achieves good realism, semantic consistency, and correctness across the heterogeneous urban styles in 330 US cities. Codes and datasets are released at?..作者: OGLE 時間: 2025-3-30 09:14
Allgemeinchirurgische Operationena high-quality Mobile-Spec dataset to support our research, and our experiments validate the effectiveness of Lr-MSI in the tone enhancement task. This work aims to establish a solid foundation for advancing spectral vision in mobile photography. The code is available at ..作者: 不近人情 時間: 2025-3-30 15:10
Allgemeinchirurgische Operationenetter generalization, we employ a decoder-only overall architecture and propose a bilateral cross-attention block for efficient interactions between context and spatial tokens. SpatialFormer learns transferable image representations with explicit scene understanding, where the output spatial tokens 作者: 前奏曲 時間: 2025-3-30 17:16 作者: 意外的成功 時間: 2025-3-30 23:09
Schrittmacher und Defibrillatoren,ng the language model to naturally integrate the target concept in its generated response. We apply our technique to BLIP-2 and LLaVA for personalized image captioning and further show its applicability for personalized visual question-answering. Our experiments demonstrate our ability to generalize作者: 信徒 時間: 2025-3-31 02:30
Magenresektion und Gastrektomie,s state-of-the-art results in terms of speed and accuracy. To our knowledge, this work is the first to address the scalability of BA without initialization opening new venues for initialization-free structure-from-motion.作者: 芳香一點 時間: 2025-3-31 07:13 作者: hemorrhage 時間: 2025-3-31 12:42
,Verb?nde und Boolesche Algebren,introduce a Query-Pool Regularization (QR) loss that regulates the relationship between the prompt query and the prompt pool to improve representation power. The QR loss is only applied during training time, so there is no computational overhead at inference from the QR loss. With the QR loss, our a作者: Crepitus 時間: 2025-3-31 16:48
Die Leistungsfaktoren im Betriebsprozess while significantly reducing computational demands and achieving at least a 10x speedup. SpaceJAM sets a new standard for rapid and effective image alignment, making the process more accessible and efficient. Our code is available at: ..作者: 或者發(fā)神韻 時間: 2025-3-31 19:27 作者: Anticoagulant 時間: 2025-4-1 00:57 作者: engagement 時間: 2025-4-1 04:46 作者: 詢問 時間: 2025-4-1 07:50
Eigenmittel und deren Verwendung order to narrow the gap between video-text models and human performance on RCAD, we identify a key limitation of current contrastive approaches on video-text data and introduce ., a more effective approach to learn action semantics by leveraging knowledge obtained from a pretrained large language m作者: concubine 時間: 2025-4-1 10:57
