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Ji.hwan Kim's Projects

actiondetection-afsd icon actiondetection-afsd

Code for CVPR2021 paper "Learning Salient Boundary Feature for Anchor-free Temporal Action Localization"

augmentation-corruption icon augmentation-corruption

This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".

clip icon clip

Contrastive Language-Image Pretraining

dab-detr icon dab-detr

[ICLR 2022] DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

deepmodels icon deepmodels

TensorFlow Implementation of state-of-the-art models since 2012

deformable-detr icon deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

detad icon detad

Diagnosing Error in Temporal Action Detectors (ECCV 2018)

detectron2 icon detectron2

Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

dino icon dino

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

dn-detr icon dn-detr

[CVPR 2022 Oral]Official implementation of DN-DETR

e2e-tad icon e2e-tad

[CVPR 2022] An Empirical Study of End-to-end Temporal Action Detection

elaborativerehearsal icon elaborativerehearsal

This is the official implementation of Elaborative Rehearsal for Zero-shot Action Recognition (ICCV2021)

fcos icon fcos

FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)

gcnet icon gcnet

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

gma icon gma

Learning to Estimate Hidden Motions with Global Motion Aggregation (ICCV 2021)

graph2tree-1 icon graph2tree-1

Graph4Tree is a simple example code for our EMNLP'20 Findings paper idea.

magic icon magic

Language Models Can See: Plugging Visual Controls in Text Generation

maxl icon maxl

The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].

plain-detr icon plain-detr

[ICCV2023] DETR Doesnโ€™t Need Multi-Scale or Locality Design

py-denseflow icon py-denseflow

Extract TVL1 optical flows in python (multi-process && multi-server)

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