English | 简体中文
| Image (212) | Text (130) | Audio (15) | Video (8) | Industrial Application (1) |
|---|---|---|---|---|
| Image Classification (108) | Text Generation (17) | Voice Cloning (2) | Video Classification (5) | Meter Detection (1) |
| Image Generation (26) | Word Embedding (62) | Text to Speech (5) | Video Editing (1) | - |
| Keypoint Detection (5) | Machine Translation (2) | Automatic Speech Recognition (5) | Multiple Object tracking (2) | - |
| Semantic Segmentation (25) | Language Model (30) | Audio Classification (3) | - | - |
| Face Detection (7) | Sentiment Analysis (7) | - | - | - |
| Text Recognition (17) | Syntactic Analysis (1) | - | - | - |
| Image Editing (8) | Simultaneous Translation (5) | - | - | - |
| Instance Segmentation (1) | Lexical Analysis (2) | - | - | - |
| Object Detection (13) | Punctuation Restoration (1) | - | - | - |
| Depth Estimation (2) | Text Review (3) | - | - | - |
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| module | Network | Dataset | Introduction |
|---|---|---|---|
| DriverStatusRecognition | MobileNetV3_small_ssld | 分心司机检测数据集 | |
| mobilenet_v2_animals | MobileNet_v2 | 百度自建动物数据集 | |
| repvgg_a1_imagenet | RepVGG | ImageNet-2012 | |
| repvgg_a0_imagenet | RepVGG | ImageNet-2012 | |
| resnext152_32x4d_imagenet | ResNeXt | ImageNet-2012 | |
| resnet_v2_152_imagenet | ResNet V2 | ImageNet-2012 | |
| resnet50_vd_animals | ResNet50_vd | 百度自建动物数据集 | |
| food_classification | ResNet50_vd_ssld | 美食数据集 | |
| mobilenet_v3_large_imagenet_ssld | Mobilenet_v3_large | ImageNet-2012 | |
| resnext152_vd_32x4d_imagenet | |||
| ghostnet_x1_3_imagenet_ssld | GhostNet | ImageNet-2012 | |
| rexnet_1_5_imagenet | ReXNet | ImageNet-2012 | |
| resnext50_64x4d_imagenet | ResNeXt | ImageNet-2012 | |
| resnext101_64x4d_imagenet | ResNeXt | ImageNet-2012 | |
| efficientnetb0_imagenet | EfficientNet | ImageNet-2012 | |
| efficientnetb1_imagenet | EfficientNet | ImageNet-2012 | |
| mobilenet_v2_imagenet_ssld | Mobilenet_v2 | ImageNet-2012 | |
| resnet50_vd_dishes | ResNet50_vd | 百度自建菜品数据集 | |
| pnasnet_imagenet | PNASNet | ImageNet-2012 | |
| rexnet_2_0_imagenet | ReXNet | ImageNet-2012 | |
| SnakeIdentification | ResNet50_vd_ssld | 蛇种数据集 | |
| hrnet40_imagenet | HRNet | ImageNet-2012 | |
| resnet_v2_34_imagenet | ResNet V2 | ImageNet-2012 | |
| mobilenet_v2_dishes | MobileNet_v2 | 百度自建菜品数据集 | |
| resnext101_vd_32x4d_imagenet | ResNeXt | ImageNet-2012 | |
| repvgg_b2g4_imagenet | RepVGG | ImageNet-2012 | |
| fix_resnext101_32x48d_wsl_imagenet | ResNeXt | ImageNet-2012 | |
| vgg13_imagenet | VGG | ImageNet-2012 | |
| se_resnext101_32x4d_imagenet | SE_ResNeXt | ImageNet-2012 | |
| hrnet30_imagenet | HRNet | ImageNet-2012 | |
| ghostnet_x1_3_imagenet | GhostNet | ImageNet-2012 | |
| dpn107_imagenet | DPN | ImageNet-2012 | |
| densenet161_imagenet | DenseNet | ImageNet-2012 | |
| vgg19_imagenet | vgg19_imagenet | ImageNet-2012 | |
| mobilenet_v2_imagenet | Mobilenet_v2 | ImageNet-2012 | |
| resnet50_vd_10w | ResNet_vd | 百度自建数据集 | |
| resnet_v2_101_imagenet | ResNet V2 101 | ImageNet-2012 | |
| darknet53_imagenet | DarkNet | ImageNet-2012 | |
| se_resnext50_32x4d_imagenet | SE_ResNeXt | ImageNet-2012 | |
| se_hrnet64_imagenet_ssld | HRNet | ImageNet-2012 | |
| resnext101_32x16d_wsl | ResNeXt_wsl | ImageNet-2012 | |
| hrnet18_imagenet | HRNet | ImageNet-2012 | |
| spinalnet_res101_gemstone | resnet101 | gemstone | |
| densenet264_imagenet | DenseNet | ImageNet-2012 | |
| resnext50_vd_32x4d_imagenet | ResNeXt_vd | ImageNet-2012 | |
| SpinalNet_Gemstones | |||
| spinalnet_vgg16_gemstone | vgg16 | gemstone | |
| xception71_imagenet | Xception | ImageNet-2012 | |
| repvgg_b2_imagenet | RepVGG | ImageNet-2012 | |
| dpn68_imagenet | DPN | ImageNet-2012 | |
| alexnet_imagenet | AlexNet | ImageNet-2012 | |
| rexnet_1_3_imagenet | ReXNet | ImageNet-2012 | |
| hrnet64_imagenet | HRNet | ImageNet-2012 | |
| efficientnetb7_imagenet | EfficientNet | ImageNet-2012 | |
| efficientnetb0_small_imagenet | EfficientNet | ImageNet-2012 | |
| efficientnetb6_imagenet | EfficientNet | ImageNet-2012 | |
| hrnet48_imagenet | HRNet | ImageNet-2012 | |
| rexnet_3_0_imagenet | ReXNet | ImageNet-2012 | |
| shufflenet_v2_imagenet | ShuffleNet V2 | ImageNet-2012 | |
| ghostnet_x0_5_imagenet | GhostNet | ImageNet-2012 | |
| inception_v4_imagenet | Inception_V4 | ImageNet-2012 | |
| resnext101_vd_64x4d_imagenet | ResNeXt_vd | ImageNet-2012 | |
| densenet201_imagenet | DenseNet | ImageNet-2012 | |
| vgg16_imagenet | VGG | ImageNet-2012 | |
| mobilenet_v3_small_imagenet_ssld | Mobilenet_v3_Small | ImageNet-2012 | |
| hrnet18_imagenet_ssld | HRNet | ImageNet-2012 | |
| resnext152_64x4d_imagenet | ResNeXt | ImageNet-2012 | |
| efficientnetb3_imagenet | EfficientNet | ImageNet-2012 | |
| efficientnetb2_imagenet | EfficientNet | ImageNet-2012 | |
| repvgg_b1g4_imagenet | RepVGG | ImageNet-2012 | |
| resnext101_32x4d_imagenet | ResNeXt | ImageNet-2012 | |
| resnext50_32x4d_imagenet | ResNeXt | ImageNet-2012 | |
| repvgg_a2_imagenet | RepVGG | ImageNet-2012 | |
| resnext152_vd_64x4d_imagenet | ResNeXt_vd | ImageNet-2012 | |
| xception41_imagenet | Xception | ImageNet-2012 | |
| googlenet_imagenet | GoogleNet | ImageNet-2012 | |
| resnet50_vd_imagenet_ssld | ResNet_vd | ImageNet-2012 | |
| repvgg_b1_imagenet | RepVGG | ImageNet-2012 | |
| repvgg_b0_imagenet | RepVGG | ImageNet-2012 | |
| resnet_v2_50_imagenet | ResNet V2 | ImageNet-2012 | |
| rexnet_1_0_imagenet | ReXNet | ImageNet-2012 | |
| resnet_v2_18_imagenet | ResNet V2 | ImageNet-2012 | |
| resnext101_32x8d_wsl | ResNeXt_wsl | ImageNet-2012 | |
| efficientnetb4_imagenet | EfficientNet | ImageNet-2012 | |
| efficientnetb5_imagenet | EfficientNet | ImageNet-2012 | |
| repvgg_b1g2_imagenet | RepVGG | ImageNet-2012 | |
| resnext101_32x48d_wsl | ResNeXt_wsl | ImageNet-2012 | |
| resnet50_vd_wildanimals | ResNet_vd | IFAW 自建野生动物数据集 | |
| nasnet_imagenet | NASNet | ImageNet-2012 | |
| se_resnet18_vd_imagenet | |||
| spinalnet_res50_gemstone | resnet50 | gemstone | |
| resnext50_vd_64x4d_imagenet | ResNeXt_vd | ImageNet-2012 | |
| resnext101_32x32d_wsl | ResNeXt_wsl | ImageNet-2012 | |
| dpn131_imagenet | DPN | ImageNet-2012 | |
| xception65_imagenet | Xception | ImageNet-2012 | |
| repvgg_b3g4_imagenet | RepVGG | ImageNet-2012 | |
| marine_biometrics | ResNet50_vd_ssld | Fish4Knowledge | |
| res2net101_vd_26w_4s_imagenet | Res2Net | ImageNet-2012 | |
| dpn98_imagenet | DPN | ImageNet-2012 | |
| resnet18_vd_imagenet | ResNet_vd | ImageNet-2012 | |
| densenet121_imagenet | DenseNet | ImageNet-2012 | |
| vgg11_imagenet | VGG | ImageNet-2012 | |
| hrnet44_imagenet | HRNet | ImageNet-2012 | |
| densenet169_imagenet | DenseNet | ImageNet-2012 | |
| hrnet32_imagenet | HRNet | ImageNet-2012 | |
| dpn92_imagenet | DPN | ImageNet-2012 | |
| ghostnet_x1_0_imagenet | GhostNet | ImageNet-2012 | |
| hrnet48_imagenet_ssld | HRNet | ImageNet-2012 |
| module | Network | Dataset | Introduction | Huggingface Spaces Demo |
|---|---|---|---|---|
| pixel2style2pixel | Pixel2Style2Pixel | - | 人脸转正 | |
| stgan_bald | STGAN | CelebA | 秃头生成器 | |
| styleganv2_editing | StyleGAN V2 | - | 人脸编辑 | |
| wav2lip | wav2lip | LRS2 | 唇形生成 | |
| attgan_celeba | AttGAN | Celeba | 人脸编辑 | |
| cyclegan_cityscapes | CycleGAN | Cityscapes | 实景图和语义分割结果互相转换 | |
| stargan_celeba | StarGAN | Celeba | 人脸编辑 | |
| stgan_celeba | STGAN | Celeba | 人脸编辑 | |
| ID_Photo_GEN | HRNet_W18 | - | 证件照生成 | |
| Photo2Cartoon | U-GAT-IT | cartoon_data | 人脸卡通化 | |
| U2Net_Portrait | U^2Net | - | 人脸素描化 | |
| UGATIT_100w | U-GAT-IT | selfie2anime | 人脸动漫化 | |
| UGATIT_83w | U-GAT-IT | selfie2anime | 人脸动漫化 | |
| UGATIT_92w | U-GAT-IT | selfie2anime | 人脸动漫化 | |
| animegan_v1_hayao_60 | AnimeGAN | The Wind Rises | 图像风格迁移-宫崎骏 | |
| animegan_v2_hayao_64 | AnimeGAN | The Wind Rises | 图像风格迁移-宫崎骏 | |
| animegan_v2_hayao_99 | AnimeGAN | The Wind Rises | 图像风格迁移-宫崎骏 | |
| animegan_v2_paprika_54 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
| animegan_v2_paprika_74 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
| animegan_v2_paprika_97 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
| animegan_v2_paprika_98 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
| animegan_v2_shinkai_33 | AnimeGAN | Your Name, Weathering with you | 图像风格迁移-新海诚 | |
| animegan_v2_shinkai_53 | AnimeGAN | Your Name, Weathering with you | 图像风格迁移-新海诚 | |
| msgnet | msgnet | COCO2014 | ||
| stylepro_artistic | StyleProNet | MS-COCO + WikiArt | 艺术风格迁移 | |
| stylegan_ffhq | StyleGAN | FFHQ | 图像风格迁移 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| face_landmark_localization | Face_Landmark | AFW/AFLW | 人脸关键点检测 |
| hand_pose_localization | - | MPII, NZSL | 手部关键点检测 |
| openpose_body_estimation | two-branch multi-stage CNN | MPII, COCO 2016 | 肢体关键点检测 |
| human_pose_estimation_resnet50_mpii | Pose_Resnet50 | MPII | 人体骨骼关键点检测 |
| openpose_hands_estimation | - | MPII, NZSL | 手部关键点检测 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| deeplabv3p_xception65_humanseg | deeplabv3p | 百度自建数据集 | 人像分割 |
| humanseg_server | deeplabv3p | 百度自建数据集 | 人像分割 |
| humanseg_mobile | hrnet | 百度自建数据集 | 人像分割-移动端前置摄像头 |
| humanseg_lite | shufflenet | 百度自建数据集 | 轻量级人像分割-移动端实时 |
| ExtremeC3_Portrait_Segmentation | ExtremeC3 | EG1800, Baidu fashion dataset | 轻量化人像分割 |
| SINet_Portrait_Segmentation | SINet | EG1800, Baidu fashion dataset | 轻量化人像分割 |
| FCN_HRNet_W18_Face_Seg | FCN_HRNet_W18 | - | 人像分割 |
| ace2p | ACE2P | LIP | 人体解析 |
| Pneumonia_CT_LKM_PP | U-NET+ | 连心医疗授权脱敏数据集 | 肺炎CT影像分析 |
| Pneumonia_CT_LKM_PP_lung | U-NET+ | 连心医疗授权脱敏数据集 | 肺炎CT影像分析 |
| ocrnet_hrnetw18_voc | ocrnet, hrnet | PascalVoc2012 | |
| U2Net | U^2Net | - | 图像前景背景分割 |
| U2Netp | U^2Net | - | 图像前景背景分割 |
| Extract_Line_Draft | UNet | Pixiv | 线稿提取 |
| unet_cityscapes | UNet | cityscapes | |
| ocrnet_hrnetw18_cityscapes | ocrnet_hrnetw18 | cityscapes | |
| hardnet_cityscapes | hardnet | cityscapes | |
| fcn_hrnetw48_voc | fcn_hrnetw48 | PascalVoc2012 | |
| fcn_hrnetw48_cityscapes | fcn_hrnetw48 | cityscapes | |
| fcn_hrnetw18_voc | fcn_hrnetw18 | PascalVoc2012 | |
| fcn_hrnetw18_cityscapes | fcn_hrnetw18 | cityscapes | |
| fastscnn_cityscapes | fastscnn | cityscapes | |
| deeplabv3p_resnet50_voc | deeplabv3p, resnet50 | PascalVoc2012 | |
| deeplabv3p_resnet50_cityscapes | deeplabv3p, resnet50 | cityscapes | |
| bisenetv2_cityscapes | bisenetv2 | cityscapes |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| pyramidbox_lite_mobile | PyramidBox | WIDER FACE数据集 + 百度自采人脸数据集 | 轻量级人脸检测-移动端 |
| pyramidbox_lite_mobile_mask | PyramidBox | WIDER FACE数据集 + 百度自采人脸数据集 | 轻量级人脸口罩检测-移动端 |
| pyramidbox_lite_server_mask | PyramidBox | WIDER FACE数据集 + 百度自采人脸数据集 | 轻量级人脸口罩检测 |
| ultra_light_fast_generic_face_detector_1mb_640 | Ultra-Light-Fast-Generic-Face-Detector-1MB | WIDER FACE数据集 | 轻量级通用人脸检测-低算力设备 |
| ultra_light_fast_generic_face_detector_1mb_320 | Ultra-Light-Fast-Generic-Face-Detector-1MB | WIDER FACE数据集 | 轻量级通用人脸检测-低算力设备 |
| pyramidbox_lite_server | PyramidBox | WIDER FACE数据集 + 百度自采人脸数据集 | 轻量级人脸检测 |
| pyramidbox_face_detection | PyramidBox | WIDER FACE数据集 | 人脸检测 |
| module | Network | Dataset | Introduction | Huggingface Spaces Demo |
|---|---|---|---|---|
| chinese_ocr_db_crnn_mobile | Differentiable Binarization+RCNN | icdar2015数据集 | 中文文字识别 | |
| chinese_text_detection_db_server | Differentiable Binarization | icdar2015数据集 | 中文文本检测 | |
| chinese_ocr_db_crnn_server | Differentiable Binarization+RCNN | icdar2015数据集 | 中文文字识别 | |
| Vehicle_License_Plate_Recognition | - | CCPD | 车牌识别 | |
| chinese_cht_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 繁体中文文字识别 | |
| japan_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 日文文字识别 | |
| korean_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 韩文文字识别 | |
| german_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 德文文字识别 | |
| french_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 法文文字识别 | |
| latin_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 拉丁文文字识别 | |
| cyrillic_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 斯拉夫文文字识别 | |
| multi_languages_ocr_db_crnn | Differentiable Binarization+RCNN | icdar2015数据集 | 多语言文字识别 | |
| kannada_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 卡纳达文文字识别 | |
| arabic_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 阿拉伯文文字识别 | |
| telugu_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 泰卢固文文字识别 | |
| devanagari_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 梵文文字识别 | |
| tamil_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 泰米尔文文字识别 |
| module | Network | Dataset | Introduction | Huggingface Spaces Demo |
|---|---|---|---|---|
| realsr | LP-KPN | RealSR dataset | 图像/视频超分-4倍 | |
| deoldify | GAN | ILSVRC 2012 | 黑白照片/视频着色 | |
| photo_restoration | 基于deoldify和realsr模型 | - | 老照片修复 | |
| user_guided_colorization | siggraph | ILSVRC 2012 | 图像着色 | |
| falsr_c | falsr_c | DIV2k | 轻量化超分-2倍 | |
| dcscn | dcscn | DIV2k | 轻量化超分-2倍 | |
| falsr_a | falsr_a | DIV2k | 轻量化超分-2倍 | |
| falsr_b | falsr_b | DIV2k | 轻量化超分-2倍 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| solov2 | - | COCO2014 | 实例分割 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| faster_rcnn_resnet50_coco2017 | faster_rcnn | COCO2017 | |
| ssd_vgg16_512_coco2017 | SSD | COCO2017 | |
| faster_rcnn_resnet50_fpn_venus | faster_rcnn | 百度自建数据集 | 大规模通用目标检测 |
| ssd_vgg16_300_coco2017 | |||
| yolov3_resnet34_coco2017 | YOLOv3 | COCO2017 | |
| yolov3_darknet53_pedestrian | YOLOv3 | 百度自建大规模行人数据集 | 行人检测 |
| yolov3_mobilenet_v1_coco2017 | YOLOv3 | COCO2017 | |
| ssd_mobilenet_v1_pascal | SSD | PASCAL VOC | |
| faster_rcnn_resnet50_fpn_coco2017 | faster_rcnn | COCO2017 | |
| yolov3_darknet53_coco2017 | YOLOv3 | COCO2017 | |
| yolov3_darknet53_vehicles | YOLOv3 | 百度自建大规模车辆数据集 | 车辆检测 |
| yolov3_darknet53_venus | YOLOv3 | 百度自建数据集 | 大规模通用检测 |
| yolov3_resnet50_vd_coco2017 | YOLOv3 | COCO2017 |
| module | Network | Dataset | Introduction | Huggingface Spaces Demo |
|---|---|---|---|---|
| MiDaS_Large | - | 3D Movies, WSVD, ReDWeb, MegaDepth | ||
| MiDaS_Small | - | 3D Movies, WSVD, ReDWeb, MegaDepth, etc. |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| ernie_gen | ERNIE-GEN | - | 面向生成任务的预训练-微调框架 |
| ernie_gen_poetry | ERNIE-GEN | 开源诗歌数据集 | 诗歌生成 |
| ernie_gen_couplet | ERNIE-GEN | 开源对联数据集 | 对联生成 |
| ernie_gen_lover_words | ERNIE-GEN | 网络情诗、情话数据 | 情话生成 |
| ernie_tiny_couplet | Eernie_tiny | 开源对联数据集 | 对联生成 |
| ernie_gen_acrostic_poetry | ERNIE-GEN | 开源诗歌数据集 | 藏头诗生成 |
| Rumor_prediction | - | 新浪微博中文谣言数据 | 谣言预测 |
| plato-mini | Unified Transformer | 十亿级别的中文对话数据 | 中文对话 |
| plato2_en_large | plato2 | 开放域多轮数据集 | 超大规模生成式对话 |
| plato2_en_base | plato2 | 开放域多轮数据集 | 超大规模生成式对话 |
| CPM_LM | GPT-2 | 自建数据集 | 中文文本生成 |
| unified_transformer-12L-cn | Unified Transformer | 千万级别中文会话数据 | 人机多轮对话 |
| unified_transformer-12L-cn-luge | Unified Transformer | 千言对话数据集 | 人机多轮对话 |
| reading_pictures_writing_poems | 多网络级联 | - | 看图写诗 |
| GPT2_CPM_LM | 问答类文本生成 | ||
| GPT2_Base_CN | 问答类文本生成 |
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| module | Network | Dataset | Introduction |
|---|---|---|---|
| transformer_zh-en | Transformer | CWMT2021 | 中文译英文 |
| transformer_en-de | Transformer | WMT14 EN-DE | 英文译德文 |
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| module | Network | Dataset | Introduction |
|---|---|---|---|
| chinese_electra_small | |||
| chinese_electra_base | |||
| roberta-wwm-ext-large | roberta-wwm-ext-large | 百度自建数据集 | |
| chinese-bert-wwm-ext | chinese-bert-wwm-ext | 百度自建数据集 | |
| lda_webpage | LDA | 百度自建网页领域数据集 | |
| lda_novel | |||
| bert-base-multilingual-uncased | |||
| rbt3 | |||
| ernie_v2_eng_base | ernie_v2_eng_base | 百度自建数据集 | |
| bert-base-multilingual-cased | |||
| rbtl3 | |||
| chinese-bert-wwm | chinese-bert-wwm | 百度自建数据集 | |
| bert-large-uncased | |||
| slda_novel | |||
| slda_news | |||
| electra_small | |||
| slda_webpage | |||
| bert-base-cased | |||
| slda_weibo | |||
| roberta-wwm-ext | roberta-wwm-ext | 百度自建数据集 | |
| bert-base-uncased | |||
| electra_large | |||
| ernie | ernie-1.0 | 百度自建数据集 | |
| simnet_bow | BOW | 百度自建数据集 | |
| ernie_tiny | ernie_tiny | 百度自建数据集 | |
| bert-base-chinese | bert-base-chinese | 百度自建数据集 | |
| lda_news | LDA | 百度自建新闻领域数据集 | |
| electra_base | |||
| ernie_v2_eng_large | ernie_v2_eng_large | 百度自建数据集 | |
| bert-large-cased |
| module | Network | Dataset | Introduction | Huggingface Spaces Demo |
|---|---|---|---|---|
| ernie_skep_sentiment_analysis | SKEP | 百度自建数据集 | 句子级情感分析 | |
| emotion_detection_textcnn | TextCNN | 百度自建数据集 | 对话情绪识别 | |
| senta_bilstm | BiLSTM | 百度自建数据集 | 中文情感倾向分析 | |
| senta_bow | BOW | 百度自建数据集 | 中文情感倾向分析 | |
| senta_gru | GRU | 百度自建数据集 | 中文情感倾向分析 | |
| senta_lstm | LSTM | 百度自建数据集 | 中文情感倾向分析 | |
| senta_cnn | CNN | 百度自建数据集 | 中文情感倾向分析 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| DDParser | Deep Biaffine Attention | 搜索query、网页文本、语音输入等数据 | 句法分析 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| transformer_nist_wait_1 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-1策略 |
| transformer_nist_wait_3 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-3策略 |
| transformer_nist_wait_5 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-5策略 |
| transformer_nist_wait_7 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-7策略 |
| transformer_nist_wait_all | transformer | NIST 2008-中英翻译数据集 | 中译英-waitk=-1策略 |
| module | Network | Dataset | Introduction | Huggingface Spaces Demo |
|---|---|---|---|---|
| jieba_paddle | BiGRU+CRF | 百度自建数据集 | jieba使用Paddle搭建的切词网络(双向GRU)。同时支持jieba的传统切词方法,如精确模式、全模式、搜索引擎模式等切词模式。 | |
| lac | BiGRU+CRF | 百度自建数据集 | 百度自研联合的词法分析模型,能整体性地完成中文分词、词性标注、专名识别任务。在百度自建数据集上评测,LAC效果:Precision=88.0%,Recall=88.7%,F1-Score=88.4%。 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| auto_punc | Ernie-1.0 | WuDaoCorpora 2.0 | 自动添加7种标点符号 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| porn_detection_cnn | CNN | 百度自建数据集 | 色情检测,自动判别文本是否涉黄并给出相应的置信度,对文本中的色情描述、低俗交友、污秽文案进行识别 |
| porn_detection_gru | GRU | 百度自建数据集 | 色情检测,自动判别文本是否涉黄并给出相应的置信度,对文本中的色情描述、低俗交友、污秽文案进行识别 |
| porn_detection_lstm | LSTM | 百度自建数据集 | 色情检测,自动判别文本是否涉黄并给出相应的置信度,对文本中的色情描述、低俗交友、污秽文案进行识别 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| ge2e_fastspeech2_pwgan | FastSpeech2 | AISHELL-3 | 中文语音克隆 |
| lstm_tacotron2 | LSTM、Tacotron2、WaveFlow | AISHELL-3 | 中文语音克隆 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| transformer_tts_ljspeech | Transformer | LJSpeech-1.1 | 英文语音合成 |
| fastspeech_ljspeech | FastSpeech | LJSpeech-1.1 | 英文语音合成 |
| fastspeech2_baker | FastSpeech2 | Chinese Standard Mandarin Speech Copus | 中文语音合成 |
| fastspeech2_ljspeech | FastSpeech2 | LJSpeech-1.1 | 英文语音合成 |
| deepvoice3_ljspeech | DeepVoice3 | LJSpeech-1.1 | 英文语音合成 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| deepspeech2_aishell | DeepSpeech2 | AISHELL-1 | 中文语音识别 |
| deepspeech2_librispeech | DeepSpeech2 | LibriSpeech | 英文语音识别 |
| u2_conformer_aishell | Conformer | AISHELL-1 | 中文语音识别 |
| u2_conformer_wenetspeech | Conformer | WenetSpeech | 中文语音识别 |
| u2_conformer_librispeech | Conformer | LibriSpeech | 英文语音识别 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| panns_cnn6 | PANNs | Google Audioset | 主要包含4个卷积层和2个全连接层,模型参数为4.5M。经过预训练后,可以用于提取音频的embbedding,维度是512 |
| panns_cnn14 | PANNs | Google Audioset | 主要包含12个卷积层和2个全连接层,模型参数为79.6M。经过预训练后,可以用于提取音频的embbedding,维度是2048 |
| panns_cnn10 | PANNs | Google Audioset | 主要包含8个卷积层和2个全连接层,模型参数为4.9M。经过预训练后,可以用于提取音频的embbedding,维度是512 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| videotag_tsn_lstm | TSN + AttentionLSTM | 百度自建数据集 | 大规模短视频分类打标签 |
| tsn_kinetics400 | TSN | Kinetics-400 | 视频分类 |
| tsm_kinetics400 | TSM | Kinetics-400 | 视频分类 |
| stnet_kinetics400 | StNet | Kinetics-400 | 视频分类 |
| nonlocal_kinetics400 | Non-local | Kinetics-400 | 视频分类 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| SkyAR | UNet | UNet | 视频换天 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| fairmot_dla34 | CenterNet | Caltech Pedestrian+CityPersons+CUHK-SYSU+PRW+ETHZ+MOT17 | 实时多目标跟踪 |
| jde_darknet53 | YOLOv3 | Caltech Pedestrian+CityPersons+CUHK-SYSU+PRW+ETHZ+MOT17 | 多目标跟踪-兼顾精度和速度 |
| module | Network | Dataset | Introduction |
|---|---|---|---|
| WatermeterSegmentation | DeepLabV3 | 水表的数字表盘分割数据集 | 水表的数字表盘分割 |