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XinNUS
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Model Details
Model Provider
XinNUS
Model Tree
Qwen/Qwen3-VL-4B-Instruct
Input Modalities
Output Modalities
Supported Functionality
This is the model used for the main Open-o3-Video + Ours comparisons, including V-STaR and general video evaluation. It is distinct from both temporal releases and from the ECCV image-mask model.
| What Acc. | When C1 | When C2 | Where C1 | Where C2 | mAM | mLGM |
|---|---|---|---|---|---|---|
| 60.7 | 26.2 | 25.8 | 33.2 | 10.5 | 36.2 | 49.8 |
All values are percentages under the paper's official V-STaR evaluation protocol. Chain1 is what–when–where; Chain2 is what–where–when.
The repository is a standard Transformers Qwen3-VL checkpoint. Its original float32 weight serialization is retained. Select bfloat16 for GPU inference when appropriate for your hardware.
python
import torchfrom transformers import AutoModelForImageTextToText, AutoProcessor model_id = "XinNUS/Generalized-CycleGRPO-SpatioTemporal-4B"model = AutoModelForImageTextToText.from_pretrained( model_id, torch_dtype=torch.bfloat16, device_map="auto").eval()processor = AutoProcessor.from_pretrained(model_id)Follow the Open-o3-Video multimodal prompting and evidence conventions. A
timestamped spatial support has the form
<obj>object_name</obj><box>[x1,y1,x2,y2]</box>at<t>time_in_seconds</t>s,
with normalized box coordinates. The main model uses the project's mixed
region-cycle interface; the optional strict single-object trajectory format
is a separate code path, not a replacement for the main evaluation prompt.
For region-conditioned captioning, use the query timestamps/boxes and marked
frame conditioning implemented in
generalized/.
For V-STaR, use the benchmark's official chained questions and scoring.
Changing the prompt, video sampling, or evidence parser can change results.
No SAMTok mask tokenizer is required for timestamped box outputs.
Similar objects, occlusion, and sparse observations can lead to incorrect identity, timestamps, or boxes. Generated evidence should not be treated as independently verified. This model inherits the Qwen3-VL architecture and tokenizer and builds on Open-o3-Video. See NOTICE and LICENSE for attribution and license terms.
Xin Zhang, Haochen Wang, Beibei Lin, Zhaoxiang Zhang, Robby T. Tan, Jason Li, and Dacheng Tao.