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Reproducing Experiment Results

All experiments conducted in the paper have corresponding scripts for reproducability inside the repository.

All experiment scripts are located in tools/experiments/*, with scripts being separated by the different shifts and VideoDA techniques.

Viper -> CityscapesSeq


Table 2: ImageDA methods on VideoDA benchmarks:

Segformer Backbone:

Experiment Training Script
HRDA + MIC ./tools/experiments/viper_csSeq/baselines/viper_csseq_mic_hrda.sh
HRDA ./tools/experiments/viper_csSeq/baselines/viper_csseq_hrda.sh
Target Only ./tools/experiments/csSeq/supervised/csSeq_supervised_hrda.sh
Source Only ./tools/experiments/viper_csSeq/baselines/viper_source_hrda.sh

DLV2 Backbone:

Experiment Training Script
HRDA + MIC ./tools/experiments/viper_csSeq/baselines/viper_csseq_mic_hrda_dlv2.sh
HRDA ./tools/experiments/viper_csSeq/pl_refinement/consis/viper_csseq_hrda_dlv2_consis.sh
Target Only ./tools/experiments/csSeq/supervised/csSeq_supervised_hrda_dlv2.sh
Source Only ./tools/experiments/viper_csSeq/baselines/viper_source_hrda_dlv2.sh

Table 3: HRDA + MIC Ablation Study

DLV2 Backbone

Experiment Training Script
HRDA - MRFusion ./tools/experiments/viper_csSeq/mic_hrda_component_ablation/viper_csseq_hrda_dlv2_no_MRFusion.sh
HRDA - MRFusion - Rare class sampling ./tools/experiments/viper_csSeq/mic_hrda_component_ablation/viper_csseq_hrda_dlv2_no_MRFusion_no_rcs.sh
HRDA - MRFusion - Rare class sampling - ImgNet feature distance reg ./tools/experiments/viper_csSeq/mic_hrda_component_ablation/viper_csseq_hrda_dlv2_no_MRFusion_no_rcs_no_imnet.sh

Table 4: Combining existing Video-DA methods with HRDA

DLV2 Backbone:

Experiment Training Script
Source Only ./tools/experiments/viper_csSeq/baselines/viper_source_hrda_dlv2.sh
HRDA ./tools/experiments/viper_csSeq/baselines/viper_csseq_mic_hrda_dlv2.sh
(TPS) HRDA + Accel + Consis Mixup + PL Refine Warp Frame tools/experiments/viper_csSeq/accel/viper_csseq_hrda_dlv2_accel_consis_mixup_warp_frame.sh
(DAVSN) HRDA + Accel + Consis Mixup + Video Discrim + PL Refine Max confidence tools/experiments/viper_csSeq/accel/viper_csseq_hrda_dlv2_accel_consis_mixup_video_discrim_consis_filter.sh
(UDA-VSS) HRDA + Accel + Video Discrim + PL Refine Consis Filter tools/experiments/viper_csSeq/video_discrim/viper_csseq_hrda_dlv2_video_discrim_consis.sh
(MOM) HRDA + Accel + Consis Mixup + PL Refine Consis Filter tools/experiments/viper_csSeq/accel/viper_csseq_hrda_dlv2_accel_consis_mixup_consis_filter.sh
HRDA + Video Discrim. ./tools/experiments/viper_csSeq/video_discrim/viper_csseq_hrda_dlv2_video_discrim.sh
HRDA + Accel + Consis Mixup tools/experiments/viper_csSeq/accel/viper_csseq_hrda_dlv2_accel_consis_mixup.sh
HRDA + PL refine Consis Filter tools/experiments/viper_csSeq/pl_refinement/consis/viper_csseq_mic_hrda_dlv2_consis.sh
HRDA + Accel + Consis Mixup + Video Discrim tools/experiments/viper_csSeq/accel/viper_csseq_hrda_dlv2_accel_consis_mixup_video_discrim.sh
HRDA + Accel + Consis Mixup + Video Discrim + PL Refine Consis Filter tools/experiments/viper_csSeq/accel/viper_csseq_hrda_dlv2_accel_consis_mixup_video_discrim_consis_filter.sh
Target Only ./tools/experiments/csSeq/supervised/csSeq_supervised_hrda_dlv2.sh


Note: [For Tables 5-8] To train with forward or backwards flow, edit FRAME_OFFSET (positive values = forward, negative values = backwards) in configs/_base_/datasets/uda_viper_CSSeq.py along with cs_train_flow_dir and cs_val_flow_dir.

Table 5: Psuedo-label Refinement on HRDA + MIC, Segformer Backbone

Segformer Backbone:

Experiment Training Script
HRDA + MIC + PL Refine Consis Filter ./tools/experiments/viper_csSeq/pl_refinement/max_conf/viper_csseq_mic_hrda_max_conf.sh
HRDA + MIC + PL Refine Max Confidence ./tools/experiments/viper_csSeq/pl_refinement/rare_class_filter/viper_csseq_mic_hrda_rare_class_filter.sh
HRDA + MIC + PL Refine Warp Frame ./tools/experiments/viper_csSeq/pl_refinement/warp_frame/viper_csseq_mic_hrda_warp_frame.sh
HRDA + MIC + PL Refine Oracle ./tools/experiments/viper_csSeq/pl_refinement/oracle/viper_csseq_mic_hrda_oracle.sh

Table 6: Psuedo-label Refinement on HRDA, Segformer Backbone

Segformer Backbone:

Experiment Training Script
HRDA + PL Refine Consis Filter ./tools/experiments/viper_csSeq/pl_refinement/consis/viper_csseq_hrda_consis.sh
HRDA + PL Refine Max Confidence ./tools/experiments/viper_csSeq/pl_refinement/max_conf/viper_csseq_hrda_max_conf.sh
HRDA + PL Refine Warp Frame ./tools/experiments/viper_csSeq/pl_refinement/warp_frame/viper_csseq_hrda_warp_frame.sh
HRDA + PL Refine Oracle ./tools/experiments/viper_csSeq/pl_refinement/oracle/viper_csseq_hrda_oracle.sh

Table 7: Psuedo-label Refinement on HRDA + MIC, DLV2 Backbone

DLV2 Backbone:

Experiment Training Script
HRDA + MIC + PL Refine Consis Filter ../tools/experiments/viper_csSeq/pl_refinement/consis/viper_csseq_mic_hrda_dlv2_consis.sh
HRDA + MIC + PL Refine Max Confidence ./tools/experiments/viper_csSeq/pl_refinement/max_conf/viper_csseq_mic_hrda_dlv2_max_conf.sh
HRDA + MIC + PL Refine Warp Frame ./tools/experiments/viper_csSeq/pl_refinement/warp_frame/viper_csseq_mic_hrda_dlv2_warp_frame.sh
HRDA + MIC + PL Refine Oracle ./tools/experiments/viper_csSeq/pl_refinement/oracle/viper_csseq_mic_hrda_dlv2_oracle.sh

Table 8: Psuedo-label Refinement on HRDA, DLV2 Backbone

Segformer Backbone:

Experiment Training Script
HRDA + PL Refine Consis Filter ./tools/experiments/viper_csSeq/pl_refinement/consis/viper_csseq_hrda_dlv2_consis.sh
HRDA + PL Refine Max Confidence ./tools/experiments/viper_csSeq/pl_refinement/max_conf/viper_csseq_hrda_dlv2_max_conf.sh
HRDA + PL Refine Warp Frame ./tools/experiments/viper_csSeq/pl_refinement/warp_frame/viper_csseq_hrda_dlv2_warp_frame.sh
HRDA + PL Refine Oracle ./tools/experiments/viper_csSeq/pl_refinement/oracle/viper_csseq_hrda_dlv2_oracle.sh

Other Shifts

SynthiaSeq -> CityscapesSeq, SynthiaSeq -> BDDVid, ViperSeq --> BDDVid experiment scripts follow directory structure as the Viper Experiments. You can find all relevant experiments reported in the paper at tools/experiments/*.