[论文速览]Open-vocabulary Object Segmentation with Diffusion Models[2301.05221]
作者: 秋刀鱼的炼丹工坊
作者简介: 经中此篇如此高深，我确实不懂。
描述: 论文题目:Guiding Text-to-Image Diffusion Model Towards Grounded Generation / Open-vocabulary Object Segmentation with Diffusion Models 论文地址:http://arxiv.org/abs/2301.05221 项目地址:https://lipurple.github.io/Grounded_Diffusion/ * 本视频旨在传递一篇论文的存在推荐感兴趣的您阅读，并不是详细介绍，受up能力限制经常出现中英混杂，散装英语等现象，请见谅。如论文报道出了偏差，欢迎各位怒斥。 ** 新论文推荐，过往论文查找，欢迎编辑这个文档： https://docs.qq.com/sheet/DSUdOTG9xWUdydVB6 *** Slides每1-2月会上传到置顶动态地址
![[论文速览]Open-vocabulary Object Segmentation with Diffusion Models[2301.05221]](/image/26c842e666376f43985f95db7e029f46f9a4105d.jpg)
![[论文夕拾]Diffusion Models for Robotics](/image/c8225b2e0a5ad69287831ab08d1663f7f213d748.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]LoRA: Low-Rank Adaptation of Large Language Models[2106.09685]](/image/2f4cb362cc5e24a347a012cfa05220728950cc9a.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]LLaMA-Adapter: Efficient Fine-tuning..Zero-init Attention[2303.16199]](/image/ff64905ff76efb4bdc968dba0fb20828d5ee895f.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]LLaVA: Visual Instruction Tuning[2304.08485]](/image/e70f51855bd470691b72d85181c90bd4742e9107.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]CLIP Dense Inference Yields Open-Vocab ... For-Free[2309.14289]](/image/040ce691f7b55db4c2ecfedfb0479f4ac529061d.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]RetNet: A Successor to Transformer for Large Language Models[2307.08621]](/image/c10d0bbc4327d0894856c5d22199fe81411b969d.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]DreamBooth: Fine Tuning Text-to-Image Diffusion Models...[2208.12242]](/image/9ff69e5a2ffad89c8320f028fbe030a233705fec.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]SODA: Bottleneck Diffusion Models for Representation Learning[2311.17901]](/image/b973a0cc9e9c340ffe3734a81f8287ca5de2dbfc.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Open Vocab. Semantic Seg. with Patch Aligned Contrastive...[2212.04994]](/image/f298a1e73d9abf4aa926658ab0355eaf98a36389.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]DiffSeg: Unsupervised Zero-Shot Seg. using Stable Diffusion[2308.12469]](/image/26182aa4695b5dbc35ce341eb0ae11260f2a46a9.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]BLIP-2 ...with Frozen Image Encoders and Large Language Models[2301.12597]](/image/0165dab78f9f9b5e55215680d3fc1b42c16491d2.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Flamingo: a Visual Language Model for Few-Shot Learning[2204.14198]](/image/a5b7b2df9b63556dec7e0bbfc59af984002df067.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Masked-attention Mask Tr. for Universal Image Segmentation[2112.01527]](/image/9340a95ed9b82a90bc26ba6f5d4ba8be4964086e.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]GENIMA: Generative Image as Action Models[2407.07875]](/image/0885284f266d5b2719f56041788ae78e88ddd365.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]VoxPoser: Composable 3D Value Maps for Robotic...[2307.05973]](/image/77dbc942572d99289d47d32f0ccb669d5876581e.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Scalable Video Object Segmentation with Simplified Framework[2308.09903]](/image/959464f0ef932a16280a9367a9a94bead0e01dc4.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Align before Fuse / ALBEF: ...[2107.07651]](/image/9f9bab856fdcc4503bab86e4d4d13f07bfabf65d.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]Large Language Models as General Pattern Machines[2307.04721]](/image/4b568f59638222ceaf92f244271acf454b82de9a.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]LongLoRA: Efficient Fine-tuning of Long-Context LLMs[2309.12307]](/image/44bf09151bc465b3f3acb8c01537857030d6cb4d.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Denoising Diffusion Probabilistic Models / DDPM[2006.11239]](/image/b34e3a1e703a0348ba6a908740da086f055c5222.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Learning to Learn with Generative Models of NN Checkpoints[2209.12892]](/image/ae47e9b9f347382b250a0bfa71800e38227f4104.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]Deconstructing Denoising Diffusion Models for SSL[2401.14404]](/image/a1fa1e1345d3cc4b48a751183547e4b36ee83bde.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]DeiT: Data-efficient Image Transformers[2012.12877]](/image/dcc355c0e181bc0795eb94f32bc610c619a3644f.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Bootstrapping Language-Image Pre-training...[2201.12086]](/image/49d17247debc220e9ed7092ebc91e1197e08359b.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Socratic Models: Zero-Shot Multimodal Reasoning[2204.00598]](/image/9a1d0f5207e1c0e779c8d580d7961ff655a244f3.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]World Models[1803.10122]](/image/62a5057288fa61f067770c6702cd65d69c46f864.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Theia: Distilling Diverse Vision Foundation Models for Robot..[2407.20179]](/image/688292fe9375bb0fa280c7ecaf87c5aba6d79d4a.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]Crossway Diffusion: Improving Diffusion-based ... via SSL[2307.01849]](/image/a865c5d2505c2d84c03a2cc7e72ae120cd5854f7.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]NeRF: Representing Scenes as Neural Radiance Fields...[2003.08934]](/image/df0dfc5f147cbe205b051703acf2faf82d0c1a9c.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]ViperGPT: Visual Inference via Python Execution for Reasoning[2303.08128]](/image/06a1c2f6646dbfe34f4c0bdec2d3f24b40227b69.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]DAT: Vision Transformer with Deformable Attention[2201.00520]](/image/e82720fd9f531018e32df9ea33690cb799e92c57.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]Toolformer: Language Models Can Teach Themselves to Use Tools[2302.04761]](/image/901deb50d98c7c34986d1b0adfa2e61a1a4454f3.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]BiFormer: Vision Transformer with Bi-Level Routing Attention[2303.08810]](/image/615293b2b427919f5e60e6cdc71f64c2e63ec45b.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文简析]Location-Aware Self-Supervised Transformers for Semantic Seg.[2212.02400]](/image/6b3596bfeeefb31a9da5e8c44de13897ccfaa33e.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]RegMixup: Mixup as a Regularizer Can Surprisingly Improve...[2206.14502]](/image/77d1c97a4cd944e19ad822be054d6a72dd9d1ca6.jpg@336w_190h_!web-video-rcmd-cover.avif)
![[论文速览]Aggregating Nested Transformers[2105.12723]](/image/d421d14158808a20d6b8f85141adce23fcf59e4a.jpg@336w_190h_!web-video-rcmd-cover.avif)
