The baseline for lighting matching must be confirmed during the project initiation phase.
Matching AI-generated shots with live-action lighting is not a problem that can be solved solely by color grading in post-production. During project initiation, the brand and the production team must jointly confirm three baselines: light source direction, color temperature range, and contrast ratio. The light source direction determines the shadow placement in the AI-generated image, the color temperature range determines the warm or cool tendency of the image, and the contrast ratio determines the transition between highlights and shadows. If these three baselines are not documented in writing during pre-production, the AI and live-action footage will look fine individually but clash when composited together in post-production.
During the project initiation phase, the brand needs to prepare a lighting reference package containing photos of the live-action location, video clips, lighting layout diagrams, and screenshots from reference films. Based on these materials, the production team should output a lighting match specification that clarifies the lighting logic to be used for the AI-generated shots, such as the key light coming from the left window, the fill light from ceiling bounce, and the background light from a right-side rim light. This specification must clearly state the shadow direction, highlight placement, and reflection intensity for each composited shot, serving as a reference document for subsequent shooting and post-production acceptance.
To determine if project approval is sufficient, check whether the team can predict the compositing effect without a final cut, relying solely on lighting descriptions and reference images. If the description only contains broad terms like "natural light" or "warm tones," post-production will likely require rework. The risk is that AI generation tools often average out lighting, easily flattening hard shadows and local highlights from live-action footage, making the composite look fake. An exception is if the brand explicitly requests stylized processing, such as a surreal or dreamy feel; in this case, lighting matching can be relaxed, but it must be specified in the creative brief in advance and signed off by all relevant parties.
Reserve lighting data for AI compositing during the shooting phase.
During live-action shooting, the cinematographer must reserve sufficient lighting data for AI composite shots rather than just pursuing a good-looking image. Specific actions include using gray cards and color charts to record on-set light sources, shooting a reference video of a gray card before each composite shot, and recording the position, power, and gel model of the lights. This data will be directly input into the AI generation workflow as a basis for controlling light direction.
The production team should set up a lighting data log on set, filling it out after every shot with details including time, weather, lighting setup, camera settings, and gray card readings. The brand representative or producer should check this log to ensure every composite shot has corresponding lighting data. If shooting spans multiple days or changes locations, lighting data must be recollected and cannot carry over from the previous day, as sun angles and ambient indoor light will change.
During shooting, also pay attention to the shadow relationship between actors and props. The shadows of virtual objects or characters in AI composite shots must align with the shadow direction of live-action objects. If an actor stands on the right side of the key light in live-action, casting a shadow to the left, the AI-generated virtual character must follow the same shadow logic. The risk is that frequent on-set lighting adjustments can easily overlook shadow direction consistency, resulting in two conflicting light source directions during post-production compositing. An exception is if the composite shot serves only as a backdrop or wide shot without direct interaction with people or objects; in this case, shadow requirements can be appropriately reduced, but the overall atmosphere must remain unified.
Process lighting information in layers during the post-production phase.
The focus of post-production compositing is the need to process lighting information in layers. The production team should split the image into a background layer, subject layer, shadow layer, and highlight layer, adjusting the lighting attributes of each layer individually. AI-generated images usually come with global illumination, but live-action footage has local light spots and reflections, and the two must be matched separately.
During specific execution, the compositor first desaturates and reduces the contrast of the AI-generated image to approximate the raw state of the live-action footage, then adds live-action lighting characteristics layer by layer using masks and light effect plugins. For example, if a window casts a light spot on a wall in the live-action footage, the compositor must manually paint or project the same light spot onto the AI background layer, adjusting its opacity and blur. This process requires repeated testing; after each adjustment, render a single comparison frame to check shadow edges, highlight clipping, and color transitions.
The brand should participate in mid-term reviews during the post-production phase rather than waiting for final delivery. The mid-term review should provide three versions of the composite sample: a version with no light effects, a basic light effects version, and a refined light effects version, allowing the brand to intuitively feel the differences in lighting matching. To judge if post-production is qualified, check whether a "floating effect" appears in the composite image, meaning there is no contact shadow between the AI object and the live-action background, or the shadow edges are too sharp. The risk is that over-pursuing lighting matching will drag out the production cycle, so an acceptance threshold must be set, such as a shadow direction deviation of no more than 5 degrees and a color temperature deviation of no more than 200K, beyond which rework is required. An exception is if the brand pursues high dynamic range or HDR effects, in which case the tolerance for lighting matching can be greater, but the standard for the final display device must be clearly defined.
The acceptance checklist must cover all dimensions of lighting matching.
Final video acceptance cannot rely solely on the overall effect; the details of lighting matching must be checked item by item. It is recommended that the brand prepare an acceptance checklist containing the following items, with a clear pass or fail judgment for each.
- Light source direction consistency, check whether the key light direction in all composited shots matches the live-action shots, which can be determined by the direction of cast shadows.
- Color temperature matching, use a color temperature meter or a reference card to confirm that the color temperature difference between the AI-generated and live-action footage is within an acceptable range.
- Shadow density and edges, check whether the shadows of AI objects have a similar density to those of live-action objects, and whether the edges transition naturally.
- Highlights and reflections, confirm whether the surfaces of AI objects have highlights or reflections that match the live-action environment, such as floor reflections or glass reflections.
- Dynamic lighting changes, if there are moving light sources or people walking in the shot, check whether the lighting changes are synchronized.
- Grain and Noise, AI footage is usually very clean, so it needs to match the film grain or sensor noise of live-action shots to avoid the image looking "too clean" and unrealistic.
During acceptance, the brand should require the production team to provide comparison screenshots of every frame and annotate the adjustment records for lighting matching. If a shot fails, it must be clarified whether the rework scope is limited to color grading or requires regenerating the AI footage. The risk is that rework may involve re-rendering, leading to increased time costs, so it is recommended to agree on a maximum number of revisions in the contract. An exception is if the brand plans to distribute the final video across multiple platforms; since different platforms have different color space requirements, acceptance must be executed to the highest standard to avoid subsequent adaptation issues.
Identify situations where AIGC commercials are not applicable in advance
Not all brand projects are suitable for AIGC commercials, and the difficulty of lighting matching is just one of the considerations. In the following situations, it is recommended to use AI-generated shots with caution or adjust project expectations.
- The live-action environment has extremely complex lighting, such as outdoor natural light, mixed multiple light sources, or frequently changing scenes, which are difficult for AI-generated footage to simulate accurately.
- Deep interaction between real actors and AI characters is required, such as handshakes, hugs, or eye contact, where even minor deviations in lighting matching will be keenly noticed by the audience.
- The brand did not provide sufficient lighting references.If the preliminary materials are incomplete, the post-production team can only guess, and the results will likely fall short of the standards.
- The delivery cycle is extremely short.Lighting matching requires repeated iterations; if time is insufficient, it is recommended to reduce the number of AI shots or switch to pure live-action shooting.
- The brand has strict standards for lighting style.For example, if there is a requirement to perfectly replicate the lighting style of a specific historical period, AI tools may not be able to achieve it.
After identifying unsuitable scenarios, the brand should proactively discuss alternative solutions with the production team, such as using CGI compositing instead of AIGC, or adjusting the shot design to reduce the difficulty of lighting matching. The risk is that forcing the use of AIGC may result in a final product that falls below expectations, damaging the brand's image. An exception is that if the brand is willing to accept stylistic deviations and bear the risk of rework, it can be attempted, but the allocation of responsibility must be clearly defined in the contract.
The capability assessment of the production team must be based on actual case studies.
When selecting a production team, do not just look at their portfolio; focus on evaluating their actual lighting matching capabilities. The brand should require the team to provide a breakdown of the lighting matching process from past projects, including comparisons of the original footage, intermediate adjustment versions, and the final product. If the team cannot provide these process files, it indicates that their production workflow may lack transparency.
During the evaluation, a test task can be designed where the team uses a piece of live-action footage and a piece of AI-generated footage to perform lighting matching, with a one-day time limit to output a single composited shot. This test can intuitively reflect the team's tool proficiency, aesthetic judgment, and problem-solving abilities. The brand should focus on the shadow direction, color temperature transitions, and detail handling in the test results, rather than just the overall effect. The risk is that the test task may consume the team's resources, so it is recommended to test only the two to three shortlisted teams. An exception is that if the team has public technical presentations or industry awards, these can serve as bonus points, but they cannot replace the actual test.
The next step is recommended to start with a small-scale test.
For brands evaluating AIGC commercials and AI product videos, it is recommended not to launch large projects directly, but to first select a 3 to 5-second shot for testing, focusing on the core difficulty of lighting matching. This test shot should include a live-action scene and an AI-generated object, with clear lighting matching standards established. After the test is completed, the brand can evaluate the production team's capabilities, project timeline, and costs before deciding whether to proceed to the full project. If the test results are not ideal, the plan can be adjusted in a timely manner to avoid greater losses. Please remember that lighting matching is the key to the success of AIGC commercials and is worth investing sufficient time and resources.
If you are preparing an AIGC commercial project, you can first organize the brief, reference visuals, product or company materials, delivery platforms, and copyright scope, and then view theAIGC video services pageto ground communication from abstract preferences to executable production boundaries.
