在图像分割任务中,Karazija等人[45]提出了一种双阶段的零样本开放词汇分割方法,利用Stable Diffusion生成大量的数据集以提高图像分割的效果;Tan等人[46]针对少样本语义分割任务提出了Diffss模型,即利用DMs对已有的支持图像进行语义掩码、涂鸦等操作,实现辅助样本的生成以提高图像的多样性。在目标检测任务中,也有相当多的...
Fix Soft Inpaint for AnimateDiff (#15148) edit-attention: deselect surrounding whitespace (#15178) chore: fix font not loaded (#15183) use natural sort in extra networks when ordering by path Fix built-in lora system bugs caused by torch.nn.MultiheadAttention (#15190) Avoid error from None...
Stable Diffuison v2.1 fromhttps://huggingface.co/stabilityai/stable-diffusion-2-1 curl -L -O https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt#curl -L -O https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly....
However, this amplifies the diffi- culty of separating the effects of image and video data on the final model. To address these shortcomings, this work presents a systematic study of methods for video data cu- ration and further introduces a general three-stage training str...
stable_diffusion_diffedit stable_diffusion_gligen stable_diffusion_k_diffusion stable_diffusion_ldm3d stable_diffusion_panorama stable_diffusion_safe stable_diffusion_sag stable_diffusion_xl __init__.py pipeline_flax_stable_diffusion_xl.py pipeline_output.py pipeline_stable_diffusion_xl.py ...
Another very important change that Forge brings isUnet Patcher. Using Unet Patcher, methods like Self-Attention Guidance, Kohya High Res Fix, FreeU, StyleAlign, Hypertile can all be implemented in about 100 lines of codes. Thanks to Unet Patcher, many new things are possible now and supporte...
Animatediff: Animate your personalized text-to-image diffusion models without specific tuning. arXiv preprint arXiv:2307.04725, 2023. 2, 3, 7, 15, 20 [31] Sonam Gupta, Arti Keshari, and Sukhendu Das. Rv-gan: Recurrent gan for unconditional video generation. In Proceedings of the IEEE/...
DiffSwap: High-Fidelity and Controllable Face Swapping via 3D-Aware Masked Diffusion. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023, p. 8568–77. Google Scholar [22] Lee S, Glasser A, Dingman B, Xia Z, Metaxas D, Neidle C, et al. ...
Relative to SDEdit-based methods, DDIM inversion-based methods [27], [29], [51], [52] have an advantage in maintaining faithfulness to the reference image due to DDIM inversion’s deterministic sampling. DiffEdit [51] automatically generates masks to mark the regions that should be edited gui...
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