Datasets:
26TCA
/
TCA-Bench

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* Accuracy of the filming description, including shot size (e.g., close-up, wide), camera angles (viewpoint orientation), and camera movement patterns (e.g., pan, zoom, static).
**Scoring Criteria (0-10):**
* **0-2 (Critical Failure)**: Complete hallucination or misses the primary element of this dimension entirely.
* **3-4 (Poor)**: Mentions the element but with significant inaccuracies or major omissions.
* **5-6 (Fair)**: Captures the general gist but lacks detail or contains noticeable minor errors.
* **7-8 (Good)**: Accurate description with good detail; only very minor or negligible omissions.
* **9-10 (Perfect)**: Comprehensive, precise, and fully aligned with the visual evidence in the GT.
**Input:**
* **Ground Truth:** {{Ground_Truth}}
* **Candidate:** {{Candidate}}
**Output Format:**
Return ONLY a JSON object with the integer scores. No explanations, no extra text.
```json
{
"subject_and_action": <int 0-10>,
"scene_and_atmosphere": <int 0-10>,
"cinematography": <int 0-10>
}
```
You are an expert video caption evaluator. Compare the Candidate Caption against the Ground Truth (GT) focusing EXCLUSIVELY on **visual details**.
**CRITICAL INSTRUCTION: IGNORE ALL SPEECH, DIALOGUE, AND AUDIO.**
Do not penalize the candidate if it omits spoken content, attributes speech to the wrong character, or fails to transcribe dialogue. This evaluation is strictly for visual fidelity.
Evaluate the Candidate Caption based on the following **3 Dimensions** derived from the VC4VG framework. Assign a score from **0 to 10** for each dimension.
**Evaluation Dimensions:**
1. **Subject & Action**:
* Accuracy of the primary subjects' descriptions, including quantity, appearance, clothing, accessories, and spatial relationships (positions and interactions).
* Accuracy of movement and temporal changes, including sequential actions (limb movements), movement paths (direction and position changes), and gradual state transitions.
2. **Scene & Atmosphere**:
* Accuracy of the setting and background description, including spatiotemporal attributes (lighting, weather, time-of-day) and geospatial layout (object placement, background scenery).
* Accuracy of the visual style and mood, including emotional ambiance (color grading, lighting mood) and artistic/rendering qualities (e.g., cinematic, grainy, vivid).
3. **Cinematography**:
* Accuracy of the filming description, including shot size (e.g., close-up, wide), camera angles (viewpoint orientation), and camera movement patterns (e.g., pan, zoom, static).
**Scoring Criteria (0-10):**
* **0-2 (Critical Failure)**: Complete hallucination or misses the primary element of this dimension entirely.
* **3-4 (Poor)**: Mentions the element but with significant inaccuracies or major omissions.
* **5-6 (Fair)**: Captures the general gist but lacks detail or contains noticeable minor errors.
* **7-8 (Good)**: Accurate description with good detail; only very minor or negligible omissions.
* **9-10 (Perfect)**: Comprehensive, precise, and fully aligned with the visual evidence in the GT.
**Input:**
* **Ground Truth:** {{Ground_Truth}}
* **Candidate:** {{Candidate}}
**Output Format:**
Return a JSON object with the scores and a brief reasoning for each:
```json
{
"subject_and_action": {
"score": <int 0-10>,
"reason": "<brief explanation>"
},
"scene_and_atmosphere": {
"score": <int 0-10>,
"reason": "<brief explanation>"
},
"cinematography": {
"score": <int 0-10>,
"reason": "<brief explanation>"
}
}
```
Evaluate the **Candidate Caption** based strictly on the provided **Ground Truth Audio JSON**.
**Evaluation Criteria:**
For each sound event in the GT, a match is counted as **correct** if both conditions hold:
1. **Event presence**: The candidate mentions the sound event (or a recognizably equivalent one). Exact wording is not required; semantic recognizability is sufficient.
2. **Source binding**: The candidate attributes the sound to the correct source category (`Foreground character`, `Off-screen character`, `Environment`).
A match is **incorrect** if the sound is absent from the candidate, or if the source category is wrong.
**Output Format:**
Return ONLY a JSON object. No extra text.
```json
{
"results": [
{"index": 0, "correct": true},
{"index": 1, "correct": false}
]
}
```
Candidate Caption:
{{Candidate}}
Ground Truth Audio JSON:
{{Ground_Truth}}
Evaluate the **Candidate Caption** based strictly on the provided **Ground Truth Audio JSON**.
**Evaluation Criteria:**
For each sound event in the GT, a match is counted as **correct** if both conditions hold:
1. **Event presence**: The candidate mentions the sound event (or a recognizably equivalent one). Exact wording is not required; semantic recognizability is sufficient.