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CVIP's Projects

lav icon lav

(CVPR 2022) A minimalistic stack for joint perception, prediction, planning and control for end-to-end self driving.

lavis icon lavis

LAVIS - A One-stop Library for Language-Vision Intelligence

lbam_pytorch icon lbam_pytorch

Pytorch re-implementation of Paper: Image Inpainting with Learnable Bidirectional Attention Maps (ICCV 2019)

lbnet icon lbnet

This repository is an official PyTorch implementation of the paper "Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive Transformer". (IJCAI 2022)

lcfcn icon lcfcn

ECCV 2018 - Where are the Blobs: Counting by Localization with Point Supervision

ld icon ld

Localization Distillation for Dense Object Detection (CVPR 2022)

ld-metric icon ld-metric

Code for the paper entitled "Towards Driving-Oriented Metric for Lane Detection Models" (CVPR 2022)

lddg icon lddg

The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization' NIPS 2020.

ldl icon ldl

Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

learn3d icon learn3d

The code repository for "Learning Pose-invariant 3D Object Reconstruction from Single-view Images"

learnable-image-resizing icon learnable-image-resizing

TF 2 implementation Learning to Resize Images for Computer Vision Tasks (https://arxiv.org/abs/2103.09950v1).

learnable-triangulation-pytorch icon learnable-triangulation-pytorch

This repository is an official PyTorch implementation of the paper "Learnable Triangulation of Human Pose" (ICCV 2019, oral). Proposed method archives state-of-the-art results in multi-view 3D human pose estimation!

learning_to_diversify icon learning_to_diversify

This is the official code repository for ICCV2021 'Learning to Diversify from Single Domain'.

legoformer icon legoformer

Attention-based block-by-block 3D object reconstruction using Transformer

lesa icon lesa

Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms

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