Overview
This repository contains the OPD-TV Qwen3-VL-8B checkpoint used for the paper's main temporal-grounding evaluation.
OPD-TV studies a supervision transfer gap: enriching the teacher's temporal evidence improves its grounding accuracy, yet the resulting student gains are non-monotonic. The method compares the same teacher across the student's original visual input and an enriched teacher view, isolating the view-induced correction from the standard same-view policy correction. Token-level cross-view compatibility then regulates how strongly this correction enters a target anchored to the same-view teacher distribution.
The student generates trajectories from its original visual input. Privileged evidence is used for teacher supervision during training; inference uses the student alone.
Released artifacts
| Artifact | Link |
|---|---|
| Model checkpoint | CewEhao/OPD-TV-Qwen3-VL-8B |
| Training data | CewEhao/OPD-TV-Training-Data |
| Training and evaluation code | Echochef/OPD-TV |
| Evaluation suite | TencentARC/TimeLens-Bench |
Evaluation
Scores are percentages.
| Dataset | mIoU | R@0.3 | R@0.5 | R@0.7 |
|---|---|---|---|---|
| Charades-STA | 52.0 | 72.7 | 57.2 | 32.5 |
| ActivityNet Captions | 54.6 | 69.5 | 60.3 | 43.2 |
| QVHighlights | 67.6 | 82.1 | 73.5 | 58.3 |
The evaluation protocol uses uniform sampling at 2 FPS, a 768-frame cap, a 14,336 visual-token cap, greedy JSON decoding, and up to 64 generated tokens. See the repository instructions for the complete TimeLens-Bench setup.
Download and use
hf download CewEhao/OPD-TV-Qwen3-VL-8B \
--local-dir models/OPD-TV-Qwen3-VL-8B
Load the checkpoint with Transformers or serve it with vLLM using --trust-remote-code.
After installing the code repository and preparing TimeLens-Bench, run its evaluation launcher:
export MODEL_PATH=CewEhao/OPD-TV-Qwen3-VL-8B
export BENCH_ROOT=/path/to/TimeLens-Bench
export OUTPUT_DIR=/path/to/opd-tv-eval
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
bash scripts/eval_opd_tv_timelens.sh
License
The checkpoint is released under the Apache License 2.0.