Papers with Code 아카이브

Depth Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 10
평가표: 14
보존된 평가 기록: 58

Depth Estimation is the task of measuring the distance of each pixel relative to the camera. Depth is extracted from either monocular (single) or stereo (multiple views of a scene) images. Traditional methods use multi-view geometry to find the relationship between the images. Newer methods can directly estimate depth by minimizing the regression loss, or by learning to generate a novel view from a sequence. The most popular benchmarks are KITTI and NYUv2. Models are typically evaluated according to a RMS metric.

Source: DIODE: A Dense Indoor and Outdoor DEpth Dataset

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

Depth Estimation

코드

https://github.com/alililia/ms_extend/tree/main/gpu_resnet

https://github.com/alinstein/Depth_estimation

https://github.com/alisha17/benchmarks

https://github.com/aljazbozic/transformerfusion

https://github.com/alpha-vllm/lumina-t2x

https://github.com/alrojo/lasagne_residual_network

https://github.com/alvarobartt/serving-pytorch-models

https://github.com/alwynmathew/monodepth-pytorch

https://github.com/amamov/vgg16-vs-resnet

https://github.com/aman-garg0001/fruit-classifier

https://github.com/amazon-research/long-short-term-transformer

https://github.com/amazon-science/long-short-term-transformer

https://github.com/ambityga/memsem

https://github.com/amdegroot/ssd.pytorch

https://github.com/amogh7joshi/engagement-detection

https://github.com/amogh7joshi/fer

https://github.com/amogh7joshi/plant-health-detection

https://github.com/andersoncarlosfs/image_classification

https://github.com/andrea-pilzer/PFN-depth

https://github.com/andreasveit/densenet-pytorch

https://github.com/andrewlstewart/StereoNet_PyTorch

https://github.com/andrijdavid/clinical-brain-interface-2020

https://github.com/angelvillar96/FaceEmoji

https://github.com/anguyen8/sam

https://github.com/anibali/dsnt-pose2d

https://github.com/aniket-patra-1998/FLOWER_RECOGNITION

https://github.com/anjandeepsahni/face_classification

https://github.com/anjandeepsahni/face_recognition

https://github.com/anjith2006/bob.paper.mcae.icb2019

https://github.com/anjith2006/bob.paper.oneclass_mccnn_2019

https://github.com/ankit-vaghela30/Google-landmark-prediction

https://github.com/anlok/depthmap-loktev

https://github.com/anoushkrit/Knowledge

https://github.com/antabangun/coex

https://github.com/antocad/FocusOnDepth

https://github.com/anujdutt9/Artistic-Style-Transfer-using-Keras-Tensorflow