FOLLY 发表于 2025-3-30 11:55:16
http://reply.papertrans.cn/25/2424/242353/242353_51.pngPolydipsia 发表于 2025-3-30 16:03:52
http://reply.papertrans.cn/25/2424/242353/242353_52.png不利 发表于 2025-3-30 17:38:24
,Exploring Conditional Multi-modal Prompts for Zero-Shot HOI Detection,nput-conditioned instance prior and a global spatial pattern prior. The former encourages the image encoder to treat instances belonging to seen or potentially unseen HOI concepts equally while the latter provides representative plausible spatial configuration of the human and object under interactiAbsenteeism 发表于 2025-3-30 22:14:11
Training-Free Video Temporal Grounding Using Large-Scale Pre-trained Models,ame video; (2) comprehend and be sensitive to the dynamic transition of events (the transition from one event to another) in the video. To address these issues, firstly, we propose leveraging large language models (LLMs) to analyze multiple sub-events contained in the query text and analyze the templymphoma 发表于 2025-3-31 04:48:55
http://reply.papertrans.cn/25/2424/242353/242353_55.pngFulsome 发表于 2025-3-31 08:22:32
FAMOUS: High-Fidelity Monocular 3D Human Digitization Using View Synthesis,ain a fully textured mesh of the given person. Through extensive experimentation on standard 3D human benchmarks, we demonstrate the superior performance of our approach in terms of both texture and geometry. Code and dataset is available at ..LANCE 发表于 2025-3-31 10:06:12
,Efficient Learning of Event-Based Dense Representation Using Hierarchical Memories with Adaptive Uption. Unlike existing works that update these memory stacks at a fixed rate, we introduce a data-adaptive update rate that recurrently keeps track of the past memory states and learns to update the corresponding memory stacks only when it has substantial new information, thereby improving the overalAnterior 发表于 2025-3-31 14:46:59
http://reply.papertrans.cn/25/2424/242353/242353_58.pngdoxazosin 发表于 2025-3-31 18:01:30
,Multi-Granularity Sparse Relationship Matrix Prediction Network for End-to-End Scene Graph Generatiix containing entity pairs most likely to form relations. Finally, a set of sparse, most probable subject-object pairs can be constructed and used for relation decoding. Experimental results on multiple datasets demonstrate that our method achieves a new state-of-the-art overall performance. Our codDeceit 发表于 2025-3-31 23:18:43
http://reply.papertrans.cn/25/2424/242353/242353_60.png