[NeurIPS 2024 Spotlight]"LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS", Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang
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Updated
Dec 30, 2024 - Python
[NeurIPS 2024 Spotlight]"LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS", Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang
An open-source toolbox for fast sampling of diffusion models. Official implementations of our works published in ICML, NeurIPS, CVPR.
🎞️ [NeurIPS'24] MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
[NeurIPS'24] Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling
[NeurIPS 2024] SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation
[NeurIPS 2024] Official code for HourVideo: 1-Hour Video Language Understanding
[NeurIPS 2024] The official implementation of HairFastGAN. A framework for virtual hairstyle fitting.
[NeurIPS 2024] Official implementation of "BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models".
[NeurIPS2024] Multiview Scene Graph (topologically representing a scene from unposed images by interconnected place and object nodes)
Official code of "Fully Explicit Dynamic Gaussian Splatting (NeurIPS 2024)"
[ NeurIPS 2024 ] The official PyTorch implementation for Learning Truncated Causal History Model for Video Restoration.
Layout Conditioned Image Generation, NeurIPS2024
A collection of papers related to Geo-spatial Information Science in NeurIPS 2024.
[NeurIPS 2024] A Novel Rank-Based Metric for Evaluating Large Language Models
[NeurIPS 2024] Official implementation of the paper "MambaLRP: Explaining Selective State Space Sequence Models".
Code and data for "ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLM" (NeurIPS 2024 Track Datasets and Benchmarks)
[NeurIPS'25] MLLM-CompBench evaluates the comparative reasoning of MLLMs with 40K image pairs and questions across 8 dimensions of relative comparison: visual attribute, existence, state, emotion, temporality, spatiality, quantity, and quality. CompBench covers diverse visual domains, including animals, fashion, sports, and scenes
[NeurIPS' 24] Official implementation of the paper "Cloud Object Detector Adaptation by Integrating Different Source Knowledge"
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