Decoding OPPO’s quest to take mobile photography to the next level

New Delhi [India], November 29 (ANI): I recently had the opportunity to sit down and discuss imaging design with Simon Liu, Global Imaging Director, OPPO. It was a fascinating look behind the curtain at how OPPO approaches its camera technology. We discussed everything from life, health, and hobbies to his focus on delivering an unmatched imaging experience for Indian users. Let me now decode OPPO’s uncompromised focus on imaging design and explain why Simon’s role is one of the most important in the mobile ecosystem.
Decoding the Game of Skin Tones:
I started by bringing up the prominent discussion about brands, including OPPO, tuning skin tones differently for various regions, especially in India. Simon confirmed that this is something they actively address. He explained that over the past two or three years, particularly since 2022, they have moved away from subjective ‘feeling’ in image evaluation. They built an internal system to make everything numerical, quantifying details like colour, brightness, sharpness, and noise. This systematic, scientific baseline, combined with user research, allows them to set real standards.
Decoding the ‘Why’ in R&D:
OPPO has always been highly praised for its cameras in India, so I asked Simon what prompted this shift to a more scientific approach. He said that while they may have been doing well, they were not always clear on the reasons for their success. The new system helps them translate those subjective user feelings into data that their engineers can use. This, he noted, allows them to strategically analyze and improve the product by knowing exactly what aspects to preserve and what needs to be changed. For them, finding the ‘why’ is the heart of R&D. It’s about setting the goal so they can move toward it systematically and efficiently.
Decoding the Subjectivity of ‘Good’ Photos:
The challenge, he pointed out, is that whether a picture is ‘good’ or ‘bad’ is highly subjective, and users often cannot articulate why they like something. For this reason, they switched to the numerical system. He shared an insightful example about the face beauty feature: in the US, users turned it off but still wanted subtle enhancements. Their actions revealed a preference they could not express, leading to a solution that addressed the issue quite well. This taught them to watch what users do, not just what they say.

Decoding the X9’s Tone and Detail Goal:
We then discussed the Find X9 series specifically. Simon highlighted that the most noticeable improvement for users would be the picture’s tone, focusing particularly on shadows. He explained that dark areas have always been a pain point for mobile sensors, with most phones overly brightening them and losing detail. A major goal for the X9 series was to preserve shadows as they naturally appear. This work was crucial for Indian skin tones, which have a wide colour spectrum, leading them to build a large database to shift colours to a more accurate map.
Decoding Edge Detection with Scientific Precision:
I asked about edge detection, and he said that feedback on edges mostly comes up with portrait mode and the bokeh effect. Enthusiasts want a clear edge to make the main subject pop and prevent the image from looking flat. The difficulty, he admitted, is the degree of tuning. If it’s too strong, the image looks ‘photoshopped’; if it’s too weak, it looks flat. He stressed that their numerical system is how they manage this pressure, following ‘the facts’ to tune variables with scientific precision.
Decoding the Importance of AI for Superior Mobile Imaging:
OPPO’s focus towards AI is anyway a strong point that separates the brand from others and further, Simon noted that they are already using AI for high efficiency in repetitive tasks, which provides a near-ready result quickly, though it has a limit and cannot achieve 100% perfection. Looking ahead, Simon also talked about a future where hardware continues to advance with higher pixel counts and processing power. The key to software improvement, however, is data points: collecting pictures and their associated tags. This gives them an infinite space to fine-tune scenes, aiming to identify classic scenes that represent hundreds of similar cases, ultimately working toward one or two universal software versions that satisfy everyone.
In the End:
Simon said their heaviest investment is still in colours. He expects future updates to continue improving colour coverage and performance in even more scenes. He confirmed this is a continuous process and a major focus, especially in India, where they have a dedicated team working on it as they are not yet totally satisfied with the results.
Interacting with Simon made me excited about the Find X9 series, which I am testing right now. I am already impressed with the results I am getting, where I can see significant improvements across images and videos. The detailed review will be out soon.